Soil-structure interaction in seismic response and structural performance: A systematic review

Abstract

This review explores the influence of soil-structure interaction (SSI) on the seismic response of structures, employing Latent Dirichlet Allocation (LDA) to identify research trends and thematic clusters. Key topics include the dynamic response of buildings, nonlinear modeling approaches, soil-foundation interaction, and performance-based seismic evaluation. SSI significantly modifies structural behavior, influencing vibration characteristics, wave propagation, and energy dissipation. Building parameters, soil stiffness, and foundation type were identified as critical factors impacting seismic performance. Advanced nonlinear modeling techniques, such as finite element analysis and optimization algorithms, have enhanced the accuracy of SSI simulations, enabling detailed assessments of soil-structure dynamics and damage probabilities. Innovations like gravel-rubber mixtures for seismic isolation and tuned mass dampers integrated with SSI were highlighted for their effectiveness in mitigating seismic impacts. The review highlights the necessity of incorporating SSI into design frameworks to address dynamic amplification, site-specific conditions, and fragility variations. However, critical gaps remain, particularly in large-scale fragility modeling, multi-hazard assessments, and experimental validations. These gaps highlight the need for further integration of SSI effects into seismic risk analyses and design codes. Future research should prioritize multi-disciplinary approaches that bridge theoretical advancements and practical applications to enhance structural resilience in seismically active regions. This study provides a comprehensive foundation for advancing SSI-informed seismic design practices and improving the safety and sustainability of infrastructure.

Keywords

soil-structure interaction seismic response latent dirichlet allocation building infrastructure review

Introduction

Soil-Structure Interaction (SSI) significantly influences the seismic response of buildings and infrastructure, with both beneficial and detrimental effects depending on various factors. SSI refers to the mutual influence between the soil and the structure during seismic events, affecting how forces are transmitted and how structures behave. Research indicates that structures on soft soils may experience increased inter-storey drifts and reduced base shear, leading to potential structural vulnerabilities (Brahma et al., 2023). Conversely, certain soil types can enhance stability, reducing seismic forces on structures (Janous et al., 2024; Krishnan and Sivakumar, 2024).

The complexity of SSI is highlighted by its dependence on soil characteristics, foundation depth, and building height, which can alter the dynamic response of structures significantly (Silvestri et al., 2024). Recent studies have further demonstrated that structure–soil–structure interaction (SSSI), especially under seismic loads, can significantly alter the dynamic response of adjacent structures, leading to amplified acceleration and shear forces due to phenomena such as pounding and foundation flexibility (Li et al., 2017; Li et al., 2017). For instance, while soft soils can amplify seismic effects, stiff soils may mitigate them, emphasizing the need for tailored engineering approaches in seismic design (Brahma et al., 2023). Understanding SSI is crucial for improving the resilience of buildings in earthquake-prone areas (Krishnan and Sivakumar, 2024; Silvestri et al., 2024).

Recent investigations have highlighted the necessity of incorporating SSI effects into seismic design practices. For example, a study demonstrated that neglecting SSI can lead to unsafe designs, particularly for structures with significant height or those located on soft soil (C Huang et al., 2021; Sadek et al., 2019). The interaction can also result in complex behaviors, such as the amplification of seismic waves, which can exacerbate the forces acting on the structure (Ge et al., 2023; Wang and Yang, 2022). Moreover, the type of foundation system plays a crucial role in how SSI affects seismic response. Structures with pile foundations, for instance, may experience different interaction effects compared to those with shallow foundations. Research has shown that the response of pile-supported structures can be significantly influenced by the soil’s dynamic properties, leading to variations in their seismic performance (Luan et al., 2015). The role of SSI is further complicated in urban environments where buildings are closely spaced. The interaction between adjacent structures through the soil can lead to additional seismic demands, necessitating a more comprehensive analysis that considers structure-soil-structure interaction (SSSI) (Zhao et al., 2022). Recent studies have underscored the seismic importance of structure-soil-structure interaction (SSSI), particularly in adjacent buildings. Abdulaziz MA et al. (2023) reviewed how SSI amplifies base displacements and extends natural periods, while Abdulaziz et al. (2024) experimentally showed that increased embedment reduces seismic effects and foundation rotation. Additionally, Abdulaziz M et al. (2023) found that taller buildings amplify displacements and accelerations in adjacent shorter ones. These findings highlight the need to account for SSSI in seismic modeling, especially in dense urban environments. This is particularly relevant in densely populated areas where multiple structures may respond collectively to seismic events, potentially increasing the risk of damage (Ada and Ayvaz, 2019; Kassas et al., 2022). Despite the substantial body of research, existing reviews on SSI tend to focus either on analytical modeling or soil mechanics without systematically categorizing structural typologies or integrating evolving trends in seismic mitigation technologies, such as tuned mass dampers (TMDs) and base-isolated systems. Additionally, there is limited use of topic modeling techniques like Latent Dirichlet Allocation (LDA) to organize the growing literature thematically and identify underexplored domains. Therefore, a key gap lies in the absence of a structured synthesis that bridges numerical methods, structural system behaviors, and emerging innovations in SSI modeling.

The purpose of this systematic review is to comprehensively analyze the state-of-the-art research on soil-structure interaction (SSI) systems under seismic conditions, with a focus on simulation techniques, frequency-domain analyses, and their implications for structural resilience. Utilizing LDA for thematic modeling, this study aims to identify dominant research trends, evaluate advanced methodologies, and highlight critical gaps in the field. While this review aims to provide a comprehensive thematic mapping of SSI-related research, certain subtopics (e.g., helical piles, soil liquefaction) are only briefly discussed due to their relatively lower frequency in the reviewed literature corpus. This review ultimately seeks to provide a robust foundation for future research and innovative design approaches that enhance seismic performance and resilience across diverse structural and geotechnical applications.

Methodology

Latent Dirichlet Allocation (LDA), introduced by Blei et al. (2003), is a probabilistic model widely utilized for topic modeling in unsupervised learning contexts. It identifies latent thematic structures within text corpora, assuming that each document consists of multiple topics, and each topic is characterized by a unique distribution of words (Pan and Xu, 2023). This flexibility makes it invaluable for analyzing vast datasets such as academic literature or social media, as it does not require labeled data (Wiranto and Uswatunnisa, 2022; Yu et al., 2019). Using Bayesian inference, LDA extracts meaningful patterns and enables insights into thematic trends, as visualized through tools like word clouds or topic distributions. Despite limitations such as the requirement for predefined topic numbers, advancements like Gaussian LDA aim to enhance its robustness and adaptability (Wu et al., 2022).

Figure 1 demonstrates how model perplexity varies with an increasing number of topics, indicating that an optimal number of topics balances model complexity and accuracy. In addition to perplexity, the figure also plots the computational cost (time elapsed), which refers to the processing time required by MATLAB to evaluate each topic configuration during the model training phase. This dual-axis presentation helps in visualizing the trade-off between model interpretability (as indicated by perplexity) and computational efficiency. As the number of topics increases, perplexity gradually rises beyond a certain threshold, suggesting diminished returns in model interpretability. The observed “elbow” at around 10 topics reflects an inflection point where adding more topics no longer significantly improves the model’s explanatory power while increasing computational demand. Meanwhile, Figure 2 reveals dominant terms across identified topics, providing a visual confirmation of the coherence and relevance of the thematic clusters, emphasizing critical keywords like “structure,” “seismic,” and “soil,” highlighting their significance in SSI-related studies. This demonstrates the validity and clarity of the topic categorization derived through LDA.

Figure 1.

Validation perplexity and time elapsed as a function of the number of topics in LDA.

Figure 2.

Word Cloud of LDA topic visualization showing four thematic clusters.

Significance of study

Despite the growing body of research on soil-structure interaction (SSI) and seismic resilience, novel methods for systematically reviewing and modeling the thematic structure of such literature remain limited. This study uniquely applies LDA to identify thematic trends, focusing on the intersection of SSI, seismic response, and structural resilience. Through incorporating advanced topic modeling, the study bridges gaps in understanding the variability across multi-disciplinary publications.

The scope of this systematic review investigates the thematic landscape of SSI research, emphasizing simulation techniques, frequency-domain analysis, and implications for structural resilience. It seeks to identify dominant research trends and gaps while providing a quantitative and qualitative basis for future explorations in the domain. The analysis particularly aims to evaluate performance-based design strategies and the integration of advanced simulation methods for seismic response analysis.

Construction of topics

The LDA modeling process for this study utilized MATLAB to determine the optimal number of topics. As demonstrated in Figure 3, specific themes like frequency-domain analysis, simulation techniques, and seismic resilience emerged prominently. These results highlight the ability of LDA to systematically categorize diverse research directions, enabling structured thematic exploration. A topic was considered “dominant” if it accounted for more than 25% of the topic probability distribution across the document corpus. This threshold was selected based on the relative thematic prevalence shown in Figure 4 and supported by topic coherence evaluation. The analysis generated the following four key topics:

(1) Dynamics of Building and Structural Response under SSI

(2) Nonlinear Modeling Approaches for SSI Analysis

(3) Soil-Foundation Interaction and Seismic Impacts

(4) Performance-Based Seismic Evaluation of SSI Systems

Figure 3.

Document topic probabilities from LDA analysis.

Figure 4.

Topic mixtures from LDA analysis depicting the distribution of four thematic topics.

The LDA algorithm assigns probabilities of word association to topics, enabling the emergence of coherent themes based on the strength of relationships between terms. For example, terms like “building,” “response,” and “structure” dominated Topic 1, aligning it with dynamic structural behavior under soil-structure interaction. Similarly, the frequency of terms such as “nonlinear,” “modeling,” and “analysis” in Topic 2 emphasized computational approaches to SSI analysis.

Additionally, Figure 4 emphasizes the variability of thematic probabilities, underscoring the interrelatedness of topics such as building dynamics and SSI effects, and validating the robustness of the topic construction. This stacked bar chart, visually represents the proportion of each topic across analyzed documents, showcasing thematic distributions and reinforcing the study’s findings on dominant themes.

Identification of Keywords, Collection and Preprocessing of Articles

The literature search, conducted on Scopus, utilized the keywords “soil-structure interaction,” “SSI,” “seismic response,” and “buildings,” yielding a total of 449 results. These were further refined by filtering based on document type (e.g., articles, conference papers, reviews), language (English), and accessibility (open access), resulting in 138 documents for analysis. Preprocessing involved tokenization, stop-word removal, and lemmatization to prepare the corpus for LDA modeling. MATLAB was employed for topic modeling, influencing its computational efficiency and visualization capabilities. Figure 5 illustrates the distribution of publications over the years, with a noticeable surge in recent contributions, highlighting the increasing academic interest in SSI-related research. Notably, the reviewed publications were limited to the period from 2020 to 2024 to reflect recent advancements and trends in SSI-related research. This structured approach ensures comprehensive coverage of relevant literature, facilitating accurate and insightful topic modeling outcomes. The combination of preprocessing and refined data ensures a high-quality dataset for meaningful analysis.

Figure 5.

Frequency of reviewed publications over the past 5 years in terms of types and years.

Discussions

Topic 1: Dynamics of building and structural response under SSI

The dynamic response of buildings is significantly influenced by the interaction between structural systems and their supporting soil, commonly referred to as soil-structure interaction (SSI). This phenomenon modifies the seismic behavior of buildings by altering vibration characteristics, wave propagation, and energy dissipation mechanisms compared to rigid-base assumptions. Building parameters such as height, mass, and stiffness play a critical role in dictating the extent of SSI effects. For instance, taller and more flexible buildings often exhibit amplified lateral displacements and inter-story drifts due to resonance effects with soil deformation (Awchat and Monde, 2021; SA ; Ismail et al., 2020b). The interaction between soil and foundation systems introduces foundation rocking, elongation of fundamental periods, and redistribution of internal forces, particularly in soft soils (Amendola and Pitilakis, 2023; Zhang and Far, 2022). Research highlights that SSI often increases system flexibility and amplifies structural responses under seismic excitation, particularly for buildings on deformable or liquefiable soils (Alzabeebee and Forcellini, 2021; Mina and Forcellini, 2020). Advanced numerical simulations reveal that soil deformability induces complex dynamic interactions, resulting in significant variations in base shear, rocking moments, and lateral displacements (Echebba et al., 2021; Shadlou and Bhattacharya, 2022). Furthermore, studies incorporating SSI effects in multi-story buildings indicate a pronounced influence of building mass distribution and foundation flexibility on seismic resilience (Bian and Wang, 2024; Du et al., 2023). Analytical and experimental investigations underscore the role of foundation type, soil stiffness, and wave propagation characteristics in dictating the overall system response (Elias and Beer, 2024; Pauselli et al., 2022). Critical to these findings are the implications for design practices, which must consider SSI to avoid underestimating seismic demand and ensure structural safety, particularly for mid-rise and high-rise structures (Askouni, 2024; Kontoni and Farghaly, 2023). The inclusion of SSI effects is particularly crucial for site-specific scenarios, as it reveals discrepancies in dynamic amplification factors and fragility estimates derived from conventional fixed-base models (Forcellini, 2021b; Saddouki et al., 2023). These studies collectively demonstrate that neglecting SSI can lead to unsafe or overly conservative designs, emphasizing the necessity for robust modeling approaches that integrate soil and structural dynamics (Bapir et al., 2023; Koronides et al., 2024). The increasing application of advanced computational tools, such as finite element and hybrid models, has enhanced the predictive accuracy of SSI phenomena, further bridging the gap between theoretical frameworks and practical engineering applications (Bian and Wang, 2024; Elias and Beer, 2024). Thus, integrating SSI effects into design codes and seismic risk assessments remains a pivotal step toward improving the resilience of urban infrastructure.

The integration of SSI effects into seismic risk assessments and design codes not only accounts for the intricate interaction between the soil and structural elements but also highlights the influence of localized site conditions on the dynamic response of buildings. For example, non-linear behavior of soft soils can lead to amplification of seismic waves, significantly affecting structures with flexible foundations (Zapata-Franco et al., 2023). Studies employing advanced modeling techniques have shown that SSI can modify vibration modes and energy dissipation pathways, particularly under complex loading scenarios such as mainshock-aftershock sequences or near-fault ground motions (Saddouki et al., 2023; Yang et al., 2021). Furthermore, SSI significantly impacts the efficiency of vibration control measures, such as tuned mass dampers, underscoring the need for precise parameter optimization to achieve effective seismic mitigation (Dai et al., 2021).

The role of SSI in wave propagation and energy distribution has also been examined in the context of layered soils and irregular subsurface conditions, which can result in anisotropic stress distributions and differential settlements (Chen et al., 2024; Xiong et al., 2024). Fragility analyses incorporating SSI reveal higher probabilities of structural damage in soft soil conditions, further emphasizing the importance of detailed site response analyses (Z-K Huang et al., 2021). These findings are particularly relevant for urban-scale seismic risk assessments, where large building portfolios and diverse soil conditions necessitate robust and scalable modeling frameworks (Amendola and Pitilakis, 2023; Pitilakis et al., 2024). In addition to seismic considerations, SSI has profound implications for structural health monitoring and retrofitting strategies. Dynamic system identification techniques have demonstrated the potential to capture changes in building stiffness and base conditions influenced by SSI, thereby improving diagnostic accuracy (Karatzetzou et al., 2021). Similarly, the development of probabilistic frameworks for SSI-influenced fragility and resilience assessments has advanced the understanding of long-term performance under variable seismic loading conditions (Fu et al., 2020; Qiu et al., 2024).

The impact of soil-structure interaction (SSI) on the dynamic response of buildings has been explored extensively in the literature, with a focus on the relationship between structural elements and their interaction under seismic excitation. While the previous discussion highlighted many significant studies, Table 1 provides an overview of additional key references which emphasize various aspects of SSI, such as its influence on structural elements like foundations and superstructures, as well as the dynamic interactions during seismic events.

Table 1.

SSI impacts on dynamic response of buildings, structural elements, and interaction under seismic excitation.

SSI impact on dynamic response of buildings	Impact on structural elements	Interaction under seismic excitation	Reference
Demonstrates the dynamic influence of subsoil properties on the building’s overall vibration modes.	Evaluates changes in material properties and their contribution to SSI effects under dynamic loading.	Highlights the amplification of vibrations due to SSI during mining-induced shocks.	(Zajac et al., 2024)
Assesses the seismic resilience of large liquefied natural gas (LNG) tanks built on liquefiable soil and highlights SSI’s role in structural deformation.	Identifies stress concentrations and pile bending moments in response to liquefied soil conditions.	Reveals the transition between inertial and kinematic interactions under increasing soil liquefaction depths.	(Sharari et al., 2022)
Explores natural frequency shifts in offshore wind turbines caused by SSI effects under wave loads.	Demonstrates the impact of nacelle inertia and foundation flexibility on structural stability.	Considers the interaction between soil stiffness variations and the wave-structure-soil dynamic system.	(Pezeshki et al., 2023)
Analyzes SSI-induced alterations in lateral displacements and interstory drift ratios in braced RC buildings.	Compares the efficiency of column versus shear wall bracing systems in reducing lateral drift.	Explores different soil types (rock, dense, stiff, soft) and their interaction with structural elements under seismic loads.	(Razzouk et al., 2023)
Validates numerical models of SSI effects using monitoring data from a masonry school building damaged by the Central Italy earthquake.	Considers the role of foundation flexibility and SSI in influencing incremental damage patterns.	Demonstrates the role of compliant-base models in accurately simulating incremental damage and shear force-displacement relationships during seismic sequences.	(Brunelli et al., 2021)
Quantifies the impact of rotor eccentricity on wind turbine tower performance, emphasizing SSI-induced stability variations.	Highlights the role of flexible turbine blades in altering higher modes due to SSI effects.	Explores the influence of pulse-like ground motions on seismic fragility estimates, emphasizing rotor inertia.	(Ali et al., 2021)
Provides insights into how nonlinear SSI mechanisms influence resonance phenomena in reinforced concrete frames.	Examines local damage patterns arising from SSI-induced flexibilities in the soil-foundation system.	Demonstrates the amplification of base shear and deformation due to resonance effects under seismic loading.	(Mourlas et al., 2020)
Demonstrated that SSI modifies vibration modes and reduces peak responses for buildings near railway defects.	Highlighted floor amplification effects in rigid vs. flexible footings.	Indicated critical thresholds of building response due to railway-induced vibrations.	(López-Mendoza et al., 2020)
Studied tuned mass dampers’ effectiveness in controlling near-fault seismic responses with SSI.	Enhanced mass damper efficiency when SSI was considered.	Found variability in control effectiveness due to directivity effects in near-fault zones.	(Elias et al., 2020)
Addressed the influence of SSI on long-period seismic responses in mid-rise RC buildings.	Suggested recalibration of base shear coefficients for buildings on soft soils.	Showed increased displacement demand due to SSI in OS1 and OS2 regions.	(Yoshida et al., 2021)
Analyzed tuned mass dampers in tall steel buildings with and without SSI.	Revealed suboptimal damping efficiency without SSI inclusion.	Illustrated greater effectiveness of multiple dampers with SSI in reducing seismic displacements.	(Khazaei et al., 2020)

Topic 2: Nonlinear modeling approaches for SSI analysis

Nonlinear modeling approaches for seismic soil-structure interaction (SSI) analysis have emerged as critical methodologies for accurately capturing the complexities of SSI behavior under earthquake excitations. These approaches incorporate advanced numerical techniques to model the nonlinearities in both soil and structural systems, facilitating a detailed assessment of seismic performance and damage. Nonlinear SSI analysis often integrates fragility curve methodologies to quantify probabilistic damage outcomes, particularly for systems like pile foundations, modular buildings, and reinforced concrete structures. Techniques such as the Gaussian Process surrogate model (Su et al., 2021) and high-performance computing frameworks (Riaz et al., 2021) have significantly enhanced computational efficiency, allowing large-scale and high-resolution simulations. Finite element models are commonly used, as demonstrated in studies of wharf structures and modular buildings (Farajian et al., 2022), to assess the dynamic response to seismic forces and the impacts of SSI. Fragility analysis plays a pivotal role in understanding damage thresholds, as explored in studies on pile foundations under liquefaction (Forcellini, 2021a) and seismic isolation systems (Pitilakis et al., 2021). Moreover, methodologies that include Monte Carlo simulations and adaptive neurochaotic fuzzy controllers (Jafarzadeh et al., 2023) provide insights into mitigating seismic impacts on nonlinear systems. These nonlinear models address the limitations of traditional fixed-base analyses by accounting for soil flexibility and structure-soil interaction effects, as illustrated in the seismic assessment of piloti-type buildings (Kim et al., 2021) and offshore wind turbine platforms (Kontoni and Farghaly, 2024). With the growing adoption of dynamic time history analysis, models are increasingly refined to incorporate multi-axial soil behavior, energy dissipation mechanisms, and dynamic amplification effects, as seen in studies on modular mid-story isolated structures (Shu et al., 2023) and historical masonry bridges (Shabani and Kioumarsi, 2023). The integration of domain-reduction methods (Korres et al., 2023) and optimization algorithms (Z Li et al., 2024b, 2024a) underscores the advancements in SSI modeling to enhance structural resilience and optimize design parameters. As SSI research continues to expand, particularly in dynamic environments with complex boundary conditions, these nonlinear methodologies will remain indispensable in seismic engineering, providing robust insights for design, retrofitting, and hazard mitigation.

Furthermore, advanced numerical techniques, such as those leveraging high-performance computing and multi-GPU parallel algorithms (Zhao et al., 2024), have enhanced the capacity to model SSI for large-scale and integrated underground-aboveground systems. These approaches are instrumental in capturing multidirectional seismic effects and the interaction of structural components with heterogeneous soil layers, which traditional linear methods fail to address comprehensively. Studies on geotechnical seismic isolation (Forcellini and Alzabeebee, 2023) and the use of gravel-rubber mixtures (Pitilakis et al., 2021) highlight innovative solutions to reduce seismic vulnerabilities. Similarly, the dynamic response of mid-rise and modular structures under SSI has been thoroughly investigated, showing significant effects on modal parameters and inter-story drift ratios under varying seismic inputs (S Ismail et al., 2020). Key methodologies also include fragility curve integration with nonlinear analyses to predict probabilistic damage under specific seismic scenarios, as seen in liquefaction-induced damage assessments (Forcellini, 2020) and complex shear wall systems (Aguayo et al., 2024). The coupling of soil and structural dynamics is critical in specific scenarios, such as offshore platforms under simplified pulse-like earthquakes (Konstandakopoulou et al., 2020a) and tunnels interacting with surrounding alluvial soils (Zhongkai Huang, Pitilakis et al., 2022b). These investigations demonstrate the necessity of accounting for both kinematic and inertial SSI effects to prevent underestimations of seismic demand on structural systems.

Nonlinear SSI modeling has further evolved through experimental validations, including shake table tests and operational modal analyses, to improve model accuracy for real-world applications (Park et al., 2023; Visuvasam and Chandrasekaran, 2022). Insights from these experiments have informed improved numerical simulations, as evidenced in analyses of masonry-infilled RC buildings (Forcellini, 2021c) and mid-story isolated structures in karst regions (Xiao et al., 2023). Innovative control systems, such as swarm-based parallel control for adjacent irregular buildings (Azimi and Yeznabad, 2020), and machine learning integration for blast-induced damage prediction (Abd-Elhamed et al., 2022), represent cutting-edge advancements that enhance the accuracy and applicability of nonlinear SSI models. The exploration of nonlinear modeling approaches for seismic soil-structure interaction (SSI) has further advanced with methodologies emphasizing the integration of dynamic effects, material nonlinearities, and soil heterogeneity. Nonlinear finite element modeling (Farajian et al., 2022; Hoque et al., 2023) continues to play a pivotal role in simulating complex soil-structure dynamics under seismic loads. For instance, modeling SSI in karst regions (Xiao et al., 2023) revealed how irregular geological features amplify structural responses. Similarly, the use of tuned mass dampers in monopile offshore wind turbines, incorporating pile-soil-structure interactions, has demonstrated the efficacy of tailored mitigation strategies under combined seismic and environmental loads (Kontoni and Farghaly, 2024).

Significant advancements have been observed in methodologies employing domain reduction techniques and regional-scale physics-based simulations, allowing for the realistic modeling of seismic wave propagation through heterogeneous media and its interaction with critical structures (Korres et al., 2023). Such approaches are particularly valuable in addressing multi-hazard scenarios, such as the seismic behavior of bridges in landslide-prone areas, where soil nonlinearity and structural plasticity must be accounted for simultaneously (Mantakas et al., 2023). Experimental validations, including long-term monitoring of soil-structure systems subjected to mining-induced vibrations, have contributed to refining SSI models, highlighting the impact of soil shear wave velocity and structural foundation rigidity on dynamic responses (Kuzniar et al., 2024). Research on mid-rise frame structures (SA Ismail et al., 2020a) and piloti-type buildings (Kim et al., 2021) has demonstrated the critical role of SSI in influencing base shear, inter-story drift, and overall stability, necessitating revisions in design provisions to address these effects comprehensively. Recent studies underscore the importance of incorporating nonlinear soil and structural behaviors to enhance predictions of seismic responses. Advanced numerical models, such as finite element (FE) and finite difference (FD) methods, offer high-fidelity representations of SSI dynamics, while machine learning and optimization algorithms provide new avenues for improving computational efficiency.

Table 2 highlights several nonlinear modeling techniques, their specific applications, and their effectiveness in various SSI scenarios, as illustrated in recent research. The studies referenced in the table have not been explicitly discussed in the main text and provide a complementary understanding of the methodologies used.

Table 2.

Nonlinear modeling techniques for SSI analysis.

Modeling technique	Application	Effectiveness
Finite element method (FEM) (Çetindemir and Zülfikar, 2024)	Comprehensive soil-pile-structure interaction modeling.	Validated against centrifuge test results, this method offers detailed insights into the SSI behavior but is computationally intensive, requiring significant expertise in both structural and geotechnical engineering.
Macro-element modeling (Cavalieri et al., 2022)	Simplified nonlinear soil modeling for SSI effects in displacement-based design methods.	Provides efficient and less computationally expensive alternatives for high seismic intensity scenarios, while retaining accuracy in predicting structural responses such as base shear and foundation displacement.
Convolutional neural networks (Wang et al., 2023)	Machine learning-based prediction of SSI-induced changes in structural drifts and base shear forces.	High accuracy and computational efficiency for large-scale regional seismic damage assessments, even with limited input data.
FLAC 3D nonlinear simulation (López Jiménez and Dias, 2022)	Analysis of soil inclusion systems such as piles or rigid inclusions under dynamic loading.	Demonstrated accurate modeling of dynamic structural responses, including lateral displacements and inter-story drifts, for different soil and foundation systems.
OpenSees advanced elements (Antonopoulos et al., 2022)	Seismic response assessment of highway bridges with complex soil-structure dynamics.	Capable of capturing nonlinearities in both soil and structure, showing significant improvements in displacement and drift predictions when compared to traditional linear models.
Drucker-Prager soil model (Hassanpour Yasaghi et al., 2021)	Simulation of SSI effects for rectangular water tanks subjected to seismic loading.	Accurately represents soil plasticity and structural deformations under extreme conditions, identifying the influence of soil density and elasticity on structural responses.
Particle Image Velocimetry (PIV) (He and Madabhushi, 2024a)	Experimental and numerical analysis of SSI between tunnels and adjacent buildings under seismic loading.	Effectively visualizes deformation mechanisms and accurately correlates experimental data with numerical results, providing enhanced understanding of interaction dynamics.
Nonlinear fragility analysis (Forcellini, 2022)	Evaluating resilience of base-isolated structures across diverse soil conditions.	Demonstrates the impact of soil compliance on isolation performance, emphasizing the need for tailored designs for varying soil stiffness levels.
Grasshopper optimization algorithm (Mehri et al., 2023)	Optimal design of seismic isolators in SSI systems, considering irregularities in mass distribution and seismic input.	Effectively identifies design parameters to minimize base shear and drifts, outperforming traditional iterative optimization methods in computational efficiency and reliability.

Topic 3: Soil-foundation interaction and seismic impacts

The seismic performance of structures is profoundly influenced by the interaction between the soil, foundation, and structural system, collectively termed soil-structure interaction (SSI). Different soil types exhibit varied seismic responses, with softer soils generally amplifying ground motion and increasing structural displacements and stresses (Bariker and Kolathayar, 2022). Soil-foundation dynamics are further complicated by foundation design considerations, where factors like stiffness, embedment depth, and soil saturation significantly alter seismic behavior (Tsinidis et al., 2020). Foundations on softer soils often experience increased settlement and rotation, necessitating optimization in design to account for lateral soil forces and dynamic interactions (Drygala et al., 2022). Experimental and numerical studies have demonstrated that soil-induced variability, including changes in shear modulus and damping ratio, leads to substantial differences in structural response under seismic loading (Guellil et al., 2020). The seismic performance of pile foundations is especially critical in soft or saturated soils, where inertial and kinematic interaction effects become pronounced. Laboratory experiments conducted by Fattah et al. (2021) revealed that pile spacing, soil density, and vibration frequency significantly affect both vertical and horizontal displacements of pile groups under dynamic excitation. These findings emphasize that pile group configuration and relative density play a vital role in modulating seismic wave propagation and internal forces at the pile head. Additionally, Fattah et al. (2017) demonstrated that foundations on saturated soils exhibit different displacement and pore water pressure responses compared to dry soils, particularly under steady-state dynamic loading. Their results showed a 5%–10% reduction in amplitude response on saturated soil and highlighted the importance of embedment depth and relative density in mitigating seismic settlement. These experimental studies provide valuable insight into how pile-supported systems behave under seismic loading, reinforcing the need for SSI-aware modeling in seismic design frameworks.

Additionally, SSI has been shown to modify natural frequencies, amplify displacement demands, and alter stress distributions in both shallow and deep foundations (Chaudhary, 2020). The integration of dynamic soil properties into design processes has led to advancements such as the use of geotechnical seismic isolation materials like gravel-rubber mixtures to mitigate seismic effects (Abate et al., 2023).

Lateral soil forces, typically encountered in integral bridge abutments and retaining structures, arise from cyclic seismic loading and backfill interactions. These forces significantly influence foundation performance, highlighting the importance of engineered inclusions to mitigate settlement and pressure build-up (Sigdel et al., 2023). Similarly, soil variability in liquefiable zones presents unique challenges in designing stable foundations, with studies revealing that traditional fixed-base assumptions grossly underestimate displacements and rotations (Liu et al., 2022). Advances in machine learning-based optimization, incorporating geotechnical properties into finite element models, provide promising pathways for improving SSI predictions and design accuracy (Ali et al., 2023). Design optimization for SSI conditions also requires understanding the nonlinear effects of SSI on structural performance. This includes mitigating dynamic interactions in systems like offshore platforms and nuclear reactors, where seismic resilience is achieved through innovations like tuned mass dampers and advanced foundation isolation systems (Shahbazi et al., 2020). Such approaches enable the integration of environmental considerations and structural demands, leading to safer, more sustainable infrastructure. These findings underscore the necessity of incorporating SSI effects in modern seismic codes, ensuring robust and adaptive designs for diverse geotechnical conditions (Awchat et al., 2022).

Comprehensive numerical simulations, field tests, and empirical studies continue to refine the predictive capabilities of SSI models, promoting the development of tailored engineering solutions for soil-structure systems in earthquake-prone regions (Luo et al., 2023). This integrative approach fosters resilience in both structural and geotechnical engineering domains. These integrative approaches further emphasize the interplay of soil and foundation properties in determining seismic response. For example, studies highlight that variations in soil stiffness, particularly in soft and liquefiable soils, can drastically influence the energy dissipation mechanisms and the amplitude of structural vibrations during seismic events (Qi and Knappett, 2022). Additionally, the inclusion of compressible materials such as engineered geofoam and gravel-rubber mixtures demonstrates effective mitigation of lateral forces and settlement in integral bridge abutments and shallow foundation systems, optimizing performance under cyclic loading (Sigdel et al., 2023). Recent developments also focus on coupling experimental insights with numerical models to capture the effects of foundation embedment depth and dynamic response characteristics. Such studies have revealed that deeper foundations often experience reduced rocking and lateral displacement but require precise calibration of soil-foundation interaction models for accurate predictions (Koronides et al., 2023).

Understanding the dynamic interactions between soil and structure is critical for designing infrastructure subjected to compound loading conditions, such as wind and seismic forces in offshore and coastal environments. Studies have demonstrated that soil-structure interactions can significantly amplify or dampen responses depending on the stiffness and damping characteristics of the underlying soil layers (Yang et al., 2024). The adoption of soil-structure-tuned systems, like electromagnetic dampers or energy-harvesting mechanisms, has further expanded the scope of SSI mitigation strategies (Kang et al., 2023).

As SSI research evolves, the focus on probabilistic approaches and fragility assessments further enhances the understanding of system vulnerabilities, paving the way for robust, adaptive designs in diverse geotechnical and seismic conditions (Z. Huang et al., 2022c). This comprehensive exploration of soil-foundation interaction highlights the critical need for multi-disciplinary collaboration and cutting-edge technology to address the challenges posed by varying soil conditions and seismic impacts, ensuring safer, more sustainable infrastructure for the future.

The relationship between soil behavior, foundation dynamics, and performance mechanisms under seismic conditions significantly impacts the design and resilience of structures. Soft soils are known to amplify displacement and vibration periods, causing an increase in inter-story displacement angles by 10%–30%, particularly when combined with prolonged fire durations and seismic events (Wang et al., 2024). Innovative solutions, such as gravel-rubber mixtures (GRM) used in foundations, have demonstrated their effectiveness in reducing seismic amplification, decreasing base shear by up to 50%, and enabling a “rigid-body” response that enhances structural isolation (Vratsikidis and Pitilakis, 2023). Conversely, liquefiable sandy soils amplify lateral forces, inducing settlement and uplift, with flexible foundations further exacerbating these effects, particularly in tunnel floatation scenarios where uneven settlement and structural deformation become pronounced (He and Madabhushi, 2024b). High-plasticity soils show better resistance to progressive seismic collapse compared to silty sands, with such soils improving lateral force resistance in foundations and decreasing sensitivity indices in denser configurations or reduced groundwater levels (Kakhki et al., 2022). Soil damping also plays a critical role in reducing seismic responses for structures equipped with tuned mass dampers (TMDs). Semi-rigid foundations help refine frequency responses, mitigating overestimation errors and emphasizing the need to tune TMD systems to soil-structure interaction (SSI) conditions for optimal performance (Liu et al., 2024b). Additionally, nonlinear soil behavior, such as liquefaction in sandy soils, increases structural drift ratios, whereas combined foundation designs, such as pile-raft systems, enhance load-sharing capacities and fragility resistance through energy-absorbing systems (Pirhadi et al., 2023). High-frequency ground motions exacerbate SSI effects, particularly with rigid foundations amplifying soil responses and influencing embedment designs for large basements. This highlights the necessity of site-specific analyses to address high-frequency amplification at foundation levels and optimize structural safety (Cavalieri et al., 2021). These insights underline the importance of integrating advanced SSI modeling techniques and site-specific considerations in seismic design to enhance resilience and mitigate risks. Table 3 provides a structured overview of the effects of soil behavior and foundation dynamics on seismic performance mechanisms, based on studies that integrate both experimental and computational findings. It serves as a detailed reference for understanding the complex interplay in soil-structure interaction systems under seismic conditions.

Table 3.

Overview of soil behavior, foundation dynamics, and performance mechanisms in seismic responses.

Soil behavior	Foundation dynamics	Performance mechanisms	Reference
Strong correlations observed between soil properties and pile forces in soft soils.	Reinforced foundations mitigate stress concentrations at pile-soil interfaces.	Dynamic soil improvements redistribute pile forces, reducing stress by up to 20% at pile caps under seismic loads.	(Tipsunavee et al., 2023)
Dynamic soil response affects rocking and torsion in irregular RC structures.	Asymmetric foundations intensify torsional effects, leading to non-uniform stress distribution.	Enhanced nonlinear SSI analysis improves design accuracy for irregular structures, highlighting torsional irregularity mitigation strategies.	(Poudel and Chaulagain, 2024)
Variability in soil stiffness influences vibration frequencies in reinforced concrete tunnels.	Deep tunnel foundations on soft soil exhibit greater susceptibility to seismic shaking.	Time-dependent corrosion and seismic shaking cumulatively degrade tunnel structural integrity, emphasizing the need for advanced SSI modeling.	(Antoniou et al., 2023)
Soil conditions determine lateral load distribution in MSE retaining walls.	MSE wall foundations improve lateral force resistance through reinforced backfill configurations.	Improved lateral displacement and stress response control observed with MSE wall designs, highlighting their seismic adaptability.	(Falah and Muteb, 2024)
Increased damping in soft soils aids energy dissipation in underground structures.	Flexible foundations increase damping capacity for circular tunnel systems in soft soils.	ANN-based fragility models show reliable predictions of structural responses, reducing computational costs by up to 30% compared to traditional methods.	(Zhongkai Huang, Argyroudis et al., 2022a)
Non-homogeneous soil profiles exacerbate SSI effects under strong motion.	Shallow foundations amplify SSI-induced overstrength factors in RC bridge design.	Overstrength factors significantly influenced by soil profiles, necessitating site-specific design considerations.	(Sánchez et al., 2022)
Clayey soils reduce structural frequency sensitivity to damage.	Cellular foundations offer reduced vibration transmission in medium-rise buildings.	Structural damage detection enhanced by monitoring rocking frequencies, with clayey soils providing damping advantages.	(Gaile et al., 2022)
Mine-induced seismicity affects soil behavior similarly to natural earthquakes.	Foundation vibrations strongly correlate with epicentral distances and mining parameters.	Long-term structural monitoring highlights the importance of empirical models to predict SSI effects, reducing error margins in seismic response predictions.	(Kuzniar and Tatara, 2022)

Topic 4: Performance-based seismic evaluation of SSI systems

The evaluation of soil-structure systems under seismic conditions has significantly advanced through the integration of simulation techniques, frequency-domain analyses, and a focus on structural resilience. Modern research emphasizes performance-based design strategies, considering soil-structure interaction (SSI) as a critical determinant in the overall seismic response. For instance, Gao et al. (2023) applied numerical models combining Discontinuous Deformation Analysis (DDA) and Smoothed Particle Hydrodynamics (SPH) to study failure mechanisms in heterogeneous karst formations, illustrating the stress redistribution and structural stability under variable conditions. Similarly, Fayez et al. (2022) highlighted the seismic performance of helical pile groups, emphasizing frequency and intensity effects, while Brandis et al. (2022) validated nonlinear static seismic analyses for shallow foundations, revealing reduced inter-story drifts due to compliant soil behavior.

Lin et al. (2024) further illustrated how wind and seismic load interactions influence wind turbine stability, showcasing the effectiveness of SSI in reducing dynamic response and enhancing structural safety. Advanced simulation tools, such as those explored by Shrestha et al. (2022) in nuclear reactor designs, provide insights into the optimization of friction pendulum bearings, highlighting their role in isolating rotational accelerations under multi-directional excitations.

The implications of SSI on offshore and complex structures have also been thoroughly investigated. Konstandakopoulou et al. (2020b) explored offshore platform resilience under pulse-like ground motions, emphasizing soil-pile-platform dynamics. Kolli et al. (2023) proposed offshore wind farms as sustainable seismic-resilient power sources for nuclear facilities, leveraging SSI to mitigate liquefaction risks. Additionally, Forcellini et al. (2022) demonstrated the role of SSI in the fragility assessment of subsea pipelines, highlighting the vulnerability of high-pressure systems under seismic loads.

Simulation frameworks such as ShakerMaker (Abell et al., 2022) simplify seismic motion modeling for engineering applications, bridging the gap between seismology and earthquake engineering. Such advancements align with the sensitivity analyses conducted by Mekki et al. (2022), which identified critical parameters affecting SSI response, including soil damping and structural stiffness. The work by Giarlelis et al. (2023) further substantiated the detrimental effects of SSI on ductility demand during real-world seismic events, emphasizing the need for robust design methodologies.

The exploration of soil-structure systems under seismic conditions has further expanded through specialized studies focusing on advanced modeling techniques, frequency-domain analyses, and their implications for enhancing structural resilience. For instance, Antoniou et al. (2024) evaluated the role of the Extended KDamper (EKD) in reducing seismic displacements and deck accelerations in bridge systems, emphasizing the importance of nonlinear dynamic response analyses and SSI effects. Similarly, W Li et al. (2024a, 2024b) presented a simplified approach for determining the head stiffness of semi-rigid deep foundations, showing how variations in soil stiffness impact lateral deflection and vibration frequencies, with errors in higher-order frequencies reaching up to 13%.

In nuclear infrastructure, Thakur and Desai (2022) emphasized the criticality of SSI in designing advanced Combined Pile Raft Foundations (CPRFs) to mitigate seismic risks. Their review highlighted how CPRFs reduce damage by distributing loads more effectively under dynamic conditions. Shendkar et al. (2024) explored the seismic vulnerability of infilled reinforced concrete (RC) buildings using adaptive pushover analyses, showcasing the significance of infill wall configurations in improving seismic performance metrics such as overstrength and ductility.

The behavior of complex systems like hybrid reinforced concrete-steel structures under sequential seismic events was investigated by Askouni (2023). Their findings highlighted the need for elastoplastic time-domain analyses to address the unique challenges posed by material heterogeneity and boundary conditions. Deng et al. (2023) reviewed recent advancements in structural health monitoring for bridges, emphasizing how vibration-based methods and data-driven analytics help track the dynamic responses of structures impacted by SSI.

In liquid storage and containment systems, Chaithra et al. (2023) noted that seismic-induced base shear and overturning moments in tanks are significantly influenced by soil-foundation interactions. Meanwhile, Farrag and Gucunski (2023) validated dynamic soil-structure interaction (DSSI) models for bridges subjected to traffic-induced vibrations, noting improved accuracy in response prediction compared to fixed-base assumptions.

Imran et al. (2023) extensively reviewed soil-structure interaction methodologies in mechanically stabilized earth (MSE) walls, identifying the dynamic sensitivity of lateral displacements to soil parameters. Additionally, numerical assessments by Forcellini and Tessari (2022) demonstrated the impact of seismic loading parameters on soil liquefaction and its subsequent effects on structural integrity.

Research into the dynamic response of soil-structure systems under multi-hazard scenarios has also evolved. For example, Tian et al. (2023) analyzed damping technologies for offshore wind turbines, revealing the efficiency of tuned liquid column dampers in operational conditions and rotational inertia dampers under extreme seismic loads. Naji et al. (2020) reviewed the challenges of integral abutment bridges under seismic conditions, showing the importance of considering thermal expansion and soil backfill properties in seismic design.

Through integrating these findings, contemporary studies provide a nuanced understanding of SSI’s role in diverse structural applications, emphasizing the interplay between soil and foundation behavior and its implications for seismic resilience. These research advancements highlight the need for tailored design approaches, leveraging simulation and experimental validations to address the unique challenges posed by SSI in performance-based seismic engineering. Below, Table 4 summarizes these studies, categorizing their contributions to simulation techniques, frequency-domain analyses, and implications for structural resilience.

Table 4.

Contributions to performance-based seismic evaluation of SSI systems.

Simulation techniques	Frequency-domain analyses	Implications for structural resilience	Reference
Multi-criteria decision-making (MCDM), finite element modeling	Sensitivity analysis of seismic damage increase (up to 17%)	Improved seismic retrofitting techniques for RC buildings; single steel braces preferred for beam-column joints despite high maintenance.	(Requena-Garcia-Cruz et al., 2022)
Spectrum-consistent transformation to adapt ag-based fragility curves	Distinction between site-dependent and site-independent intensity measures	Enhanced accuracy of regional risk studies and consistency in fragility assessments for different locations and soil conditions.	(Monti et al., 2024)
Direct finite element method (DFEM), 3D modeling	Analysis of subgrade reaction modulus (Ks) and deformation trends	Simplified equations for considering SSI effects in concrete building foundations; practical approach for engineers.	(Khosravifardshirazi et al., 2022)
Vibration response testing using seismic simulation shaking tables	Amplification effect of lateral vibrations observed at upper building levels	Mitigation strategies for reducing discomfort in surrounding buildings near shaking table facilities.	(Xie et al., 2023)
Analytical solutions for moment contribution ratio (MCR) under foundation rotation	Examination of static and dynamic load effects	Practical graph-based approach for determining MCR; improved understanding of foundation rotation impacts on shear wall systems.	(Bozdogan and Keskin, 2024)
Development of ideal drift response curve (IDRC) for multi-level ground motions	Use of incremental dynamic analysis (IDA) and sensitivity-based algorithms	Robust damper design for elastic-plastic MDOF structures; cost-efficient optimization strategies for diverse seismic conditions.	(Akehashi and Takewaki, 2021b)

Structural typologies in soil-structure interaction research

Research on SSI spans a range of structural typologies that demonstrate diverse dynamic behaviors under seismic loading. These responses depend on variations in geometry, stiffness, foundation systems, and damping mechanisms. While earlier discussions focused on general simulation and modeling approaches, this section categorizes SSI effects by structural type, emphasizing application-specific insights for design optimization and resilience enhancement.

SSI in bridges

SSI is a critical factor in the seismic assessment of bridges, especially those located in near-fault zones or underlain by soft soil profiles. These site conditions significantly alter dynamic behavior by affecting stiffness, damping, and modal frequencies which often leading to unanticipated seismic demands. As such, integrating SSI considerations into both the design and retrofit of bridge structures is essential.

SSI notably affects a bridge’s modal characteristics. Variations in soil stiffness can lead to changes in the system’s natural frequencies and damping ratios, potentially shifting resonance conditions during strong ground motions. Kotsoglou and Pantazopoulou (2010) and Park et al. (2022) demonstrate that soil-pile-structure interactions alter the dynamic characteristics of bridge systems, emphasizing the importance of equivalent linear site response analyses in evaluating seismic inputs and their impact on frequency content.

Bridges with unconnected spans or variable support conditions are also susceptible to differential displacements between piers, which can trigger pounding at expansion joints during seismic events. Guo et al. (2021) highlight that neglecting SSI can underestimate these displacement demands, leading to inaccurate risk assessments and insufficient mitigation measures.

Traditional seismic design approaches often fall short of capturing the complexities introduced by SSI. Studies by Dezi et al. (2012) and Kotsoglou and Pantazopoulou (2010) argue for revising seismic codes to include SSI-informed criteria, especially for long-span and elevated bridges. Zhang and Gu (2020) further emphasize that neglecting SSI in bridge modeling reduces the predictive accuracy of structural response, especially under strong ground motion.

Recent advances in computational modeling, including nonlinear time history and finite element analysis, now allow for more accurate simulation of SSI in complex bridge systems. As shown by Guo et al. (2024), these techniques enable more resilient bridge designs by explicitly accounting for the interaction between substructure and soil under seismic excitation.

Building classes: Low-, mid-, and high-rise behavior

The seismic response of buildings under SSI conditions varies substantially depending on structural height and stiffness. Low-rise buildings, due to their higher stiffness, typically exhibit less pronounced SSI effects. In contrast, mid-rise and high-rise structures are more vulnerable to dynamic amplification, period elongation, and increased inter-story drifts under seismic excitation. These differences arise due to changes in modal characteristics influenced by both soil compliance and the structural aspect ratio.

Research has shown that taller buildings constructed on soft soils are prone to significant rocking and acceleration amplification. Araz et al. (2024) demonstrated that the peak floor acceleration in high-rise buildings is considerably affected by soil type, with structures on soft soils exhibiting critical acceleration profiles, particularly between the 5th and 15th floors. Their findings indicate that SSI can either mitigate or exacerbate seismic demands depending on soil stiffness and building flexibility. Furthermore, high aspect ratio buildings were shown to be particularly sensitive to the stiffness contrast between soil and structure, requiring tailored design strategies.

These observations are supported by earlier studies highlighting that modal frequency shifts caused by SSI often lead to resonance under specific ground motion characteristics. Galvín et al. (2022) and Svedholm et al. (2015) emphasized that soil properties substantially influence the modal response of mid- and high-rise buildings, necessitating adjustments in design spectra. Tsai et al. (2016) also pointed out that varying aspect ratios lead to differentiated energy dissipation mechanisms through the foundation-soil interface, impacting the damping performance of tall buildings.

Recent advancements suggest that traditional fixed-base design assumptions are insufficient for capturing the true seismic demands on high-rise buildings. Instead, comprehensive SSI-integrated models are needed to evaluate the nonlinear interactions between soil and structure, especially for critical infrastructure in high seismic zones. Khoshnoudian et al. (2015) reinforced this need by showing that collapse capacity assessments could significantly underestimate vulnerabilities if SSI is excluded.

Therefore, seismic design practices must increasingly incorporate building class-dependent SSI analysis. The complex interaction between structural height, soil compliance, and lateral load demand necessitates a performance-based approach to accurately capture risk and enhance resilience across all building categories.

Tuned mass dampers (TMDs) and SSI effects

Tuned Mass Dampers (TMDs) serve as an effective tool for mitigating vibrations in structures subjected to dynamic loading, such as earthquakes and wind-induced oscillations. However, their performance is closely linked to the structural frequency, which can be significantly altered by SSI. The fixed-base designs of TMDs may not be optimized for scenarios where soil flexibility plays a crucial role, leading to performance discrepancies when applied in real-world conditions.

The ability of TMDs to suppress vibrations hinges on the precise tuning of their natural frequencies to match those of the primary structure. Liu et al. (2024a) note that when SSI affects a building’s natural frequency, the TMDs may become detuned, significantly diminishing their effectiveness during seismic events. Jiang et al. (2024) further emphasize that structures situated on soft soils often exhibit notable reductions in TMD performance due to shifts in modal frequencies caused by soil compliance.

Studies suggest that ignoring SSI in TMD design can lead to inadequate vibration suppression, especially in high-rise buildings where base flexibility becomes more prominent. Pan et al. (2018) and Brodersen et al. (2017) argue that traditional TMD designs fail to account for these dynamic alterations, resulting in suboptimal energy dissipation. In response, adaptive or semi-active damping strategies have been proposed, including those developed by Cao and Li (2019) and Soheili et al. (2021), which utilize machine learning and optimization techniques to retune TMDs in real time.

Recent advancements explicitly examine the effectiveness of TMDs under SSI conditions. For example, Araz (2025) demonstrated that the structure-to-soil stiffness ratio and aspect ratio significantly influence TMD performance, showing that low-rise buildings on soft soil conditions experience notable performance loss. Meanwhile, Araz (2024) introduced parallel multi-TMD systems (MTMDs), revealing that configurations tuned for soil-flexible systems provide superior vibration control, particularly when optimized for varying PGV/PGA ratios. Similarly, Araz and Elias (2024) explored different arrangements of double-TMD systems, concluding that soil stiffness and damper layout dramatically affect performance metrics, especially in near- and far-fault seismic scenarios.

Base-isolated structures and SSI

Base isolation systems are engineered to decouple a structure’s superstructure from ground motion, thereby reducing the seismic forces transmitted to the building during an earthquake. These systems utilize flexible bearings or isolators that allow horizontal movement, effectively dissipating seismic energy and improving overall structural resilience (Akehashi and Takewaki, 2021a; De Domenico et al., 2020). However, when SSI is considered, the dynamic behavior of base-isolated buildings may diverge from fixed-base assumptions, potentially compromising isolation effectiveness.

SSI modifies the interaction between isolators and subgrade soils, impacting the displacement patterns and energy dissipation of the system (Vibhute et al., 2022; Zhang et al., 2022). The soil’s mechanical properties, particularly stiffness and damping, can reduce isolator effectiveness during strong seismic events or prolonged ground shaking (Vetturayasudharsanan et al., 2023; Shi et al., 2025). These effects are especially critical in soft or heterogeneous soils, where dynamic amplification may lead to foundation uplift, asymmetric displacements, or altered structural periods (Shan et al., 2020; Zelleke et al., 2020).

Recent investigations have highlighted the need to integrate SSI effects in isolation system design frameworks. Enhanced modeling strategies, such as layered 3D isolation testing and hybrid isolation systems, have been proposed to address performance degradation under SSI conditions (Duan, 2022; Zhang et al., 2022). These approaches aim to improve seismic mitigation by optimizing isolator configurations according to soil profiles and structural demands (Kiran et al., 2022; Sabiha et al., 2023). Moreover, probabilistic assessments and time-history analyses are increasingly used to evaluate base-isolated structures on soft or liquefiable soils (Narjabadifam et al., 2024; Zelleke et al., 2020).

Studies demonstrate that overlooking SSI in base-isolated buildings can result in underestimating displacement demand, miscalculating story drifts, or overestimating safety margins (Shan et al., 2020; Shi et al., 2025). To counteract these issues, researchers advocate the adoption of adaptive isolation systems, SSI-aware response modification factors, and isolation performance maps that incorporate subsoil variability (Shan et al., 2020; Shi et al., 2025). Consequently, the integration of SSI into seismic design codes and base isolation strategies is imperative to ensure reliable performance of isolated systems across diverse geotechnical conditions.

Research gaps

Despite significant advancements in understanding soil-structure interaction (SSI) under seismic loading, several critical gaps remain unaddressed in the literature. Many studies, such as by Zapata-Franco et al. (2023), focus on the inelastic response of soil but do not explore the integration of these effects in large-scale urban risk assessments. Similarly, Du et al. (2023) investigated pile-raft systems under cyclic loading, yet the interaction mechanisms under varying subsurface conditions remain insufficiently quantified. Amendola and Pitilakis (Amendola and Pitilakis, 2023) introduced SSI effects in urban-scale fragility modeling but overlooked the influence of site amplification under complex geomorphic scenarios. Other works, such as those by Koronides et al. (2024), underline the importance of nonlinear SSI in marine jetty structures but fall short of examining its influence under multi-hazard conditions. Finally, the study by Chen et al. (2024) provides a simplified model for SSI analysis but does not validate its applicability across diverse structural typologies or field conditions. Furthermore, additional insights provided in Table 5 from the cited literature highlight the need for better integration of SSI effects on dynamic structural response in the presence of varying foundation geometries and subsurface complexities. Addressing these gaps is essential to develop practical solutions that improve the predictive capability and design resilience of structures in seismically active regions.

Table 5.

Key research areas and associated studies in SSI and seismic analysis.

Research area	Description	Reference
Simplified SSI models	Focuses on rigid base assumptions that neglect soil flexibility and interaction effects.	(Elias and Beer, 2024)
Fragility curves for urban scale	Limited application of SSI and site amplification effects in urban seismic fragility assessments.	(Amendola and Pitilakis, 2023)
Advanced energy dissipation systems	Explores the integration of tuned mass dampers with SSI under seismic loading.	(Yang et al., 2021)
Geotechnical seismic isolation techniques	Evaluates innovative materials such as gravel-rubber mixtures for seismic isolation under real-world conditions.	(Pitilakis et al., 2024)
Validation through case studies	Lack of real-world case studies validating numerical and experimental SSI models.	(Brunelli et al., 2021)

Critical insights and future directions

This review underscores the complex role of SSI in shaping seismic responses across diverse structural systems and soil conditions. From the discussed literature, several critical insights emerge. First, the incorporation of SSI significantly alters conventional design assumptions by shifting modal frequencies, amplifying displacements, and redistributing seismic demands, especially for high-rise buildings (Araz, 2024; Galvín et al., 2022). Such effects, if ignored, may lead to unsafe or overly conservative designs (Askouni, 2024; Forcellini, 2021b).

A key limitation in the current body of research is the lack of consistency in integrating nonlinear behavior and soil heterogeneity into design-based simulations. Although nonlinear modeling techniques such as finite element analysis (Farajian et al., 2022; Çetindemir and Zülfikar, 2024) and adaptive neuro-fuzzy approaches (Jafarzadeh et al., 2023) have shown promise, their adoption in large-scale practical applications remains limited. There is also a scarcity of experimental validation for complex SSI scenarios involving offshore platforms (Kontoni and Farghaly, 2024) and modular mid-story isolated buildings (Shu et al., 2023), which warrants more focused research using field monitoring or shake table tests (Park et al., 2023; Visuvasam and Chandrasekaran, 2022).

For vibration control systems like Tuned Mass Dampers (TMDs), SSI introduces tuning discrepancies due to frequency shifts, often reducing effectiveness (Liu et al., 2024b; Pan et al., 2018). While recent developments in adaptive or semi-active dampers (Cao and Li, 2019; Soheili et al., 2021) offer promising solutions, further investigation is needed to quantify their real-time performance under varied soil conditions and seismic intensities.

Another notable gap lies in the performance-based assessment of SSI in fragility modeling. Although several studies explore fragility curves for specific systems like liquefied natural gas (LNG) tanks and RC buildings (Sharari et al., 2022; Yoshida et al., 2021), few comprehensively integrate soil variability and multi-hazard scenarios into probabilistic frameworks. There is an evident need for fragility-informed SSI maps and region-specific vulnerability databases that factor in ground motion parameters such as PGV/PGA ratios (Araz, 2024; Monti et al., 2024). Looking ahead, future research should prioritize:

• Experimental and hybrid validation of SSI-integrated models, especially for irregular and adjacent structures in urban settings (Abdulaziz et al., 2024; Brunelli et al., 2021).

• Development of performance-based seismic design frameworks that incorporate SSI, soil liquefaction, and structural retrofitting strategies (Pitilakis et al., 2021; Xiao et al., 2023).

• Advancement of machine learning and optimization algorithms to automate SSI model calibration and prediction under uncertainty (Mehri et al., 2023; Wang et al., 2023).

• Creation of multi-scale simulation platforms capable of capturing the interaction of SSI with other external hazards (e.g., fire, landslide, and blast-induced shocks), as identified in Wang et al. (2024) (2024) and Abd-Elhamed et al. (2022).

Integrating these directions into future work will help close the gap between analytical modeling and practical seismic resilience, ultimately contributing to safer infrastructure across geotechnically diverse environments.

Conclusion

This systematic review demonstrates the critical influence of soil-structure interaction (SSI) on seismic response, altering key parameters such as modal frequencies, base shear, inter-story drift, and vibration damping across diverse structural systems. Through Latent Dirichlet Allocation (LDA), four major research themes were identified: building dynamics, nonlinear modeling approaches, soil-foundation interaction effects, and performance-based seismic evaluation. This thematic classification facilitated a structured synthesis of current trends, innovations, and persistent gaps.

Findings reveal that SSI can either amplify or mitigate seismic demands depending on soil properties, foundation type, and structural typology. Although advanced numerical models and optimization-based fragility assessments have improved simulation capabilities, practical implementation remains constrained by limited experimental validations, underrepresented multi-hazard scenarios, and fragmented design guidance.

• To bridge these gaps and enhance seismic resilience, the following recommendations are proposed:Develop SSI-based urban fragility maps with multi-hazard integration. Establish region-specific fragility mapping frameworks that incorporate probabilistic SSI effects, local site conditions, and compound hazard scenarios (e.g., seismic-landslide-fire) to support urban-scale risk-informed planning and design.

• Advance hybrid validation and adaptive simulation platforms. This is to promote shake table experiments, field monitoring, and digital twin technologies to validate SSI-integrated models. Coupled with multi-scale simulation environments, these can better capture SSI interactions in irregular, adjacent, or offshore structures under realistic loading conditions.

• Integrate SSI-aware design and machine learning optimization in codes. Enhance seismic design codes to incorporate SSI-informed provisions, especially for damping systems (e.g., TMDs), liquefaction-prone foundations, and performance-based metrics. Leverage machine learning and optimization tools to automate calibration, improve reliability, and support real-time resilience forecasting.

Through focusing on these three directions, future research can close the gap between analytical sophistication and practical implementation, enabling safer and smarter infrastructure in geotechnically complex and hazard-prone environments.

Footnotes

Acknowledgments

To Polytechnic University of the Philippines - Graduate School, thank you for the continuous support and fostering an environment that encouraged learning and research, impacted greatly to this study. I sincerely acknowledge the late Dr Orlean Dela Cruz, whose guidance and insights were instrumental in shaping this research. His dedication and mentorship will always be remembered.

Jhon Philip P Camayang

Juland A Padilla

Arvin R De La Cruz

Funding

The authors received no financial support for the research, authorship, and/or publication of this article.

Declaration of conflicting interests

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

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