The seismic performance of squat RC shear walls is a vital area of study in structural engineering, particularly for buildings in earthquake-prone regions [12,13]. These walls are characterized by a low aspect ratio (height-to-length ratio less than two). As a result, they behave differently under seismic loading compared to their taller, slender counterparts [14,15]. Squat shear walls are less typically used in low-rise buildings and are less understood compared to taller ones, especially regarding their unique mechanisms of failure and deformation during earthquakes [16–18]. Unlike slender walls dominated by flexural deformations, squat walls are governed by shear deformations, making them more vulnerable to shear failures, which are often brittle and catastrophic if not properly addressed in the design [19,20]. The seismic performance of squat shear walls is influenced by several factors, including material properties, wall geometry, reinforcement detailing, and loading conditions [21,22]. Understanding these factors is crucial for enhancing the seismic resilience of buildings relying on squat shear walls for lateral load resistance [23,24]. Early research on squat shear walls, such as the study by Hidalgo et al. [14], emphasized the importance of reinforcement detailing in preventing shear failures and improving ductility under cyclic loading. Subsequent studies explored various reinforcement strategies to enhance seismic performance, including the addition of steel plates to improve energy dissipation and shear strength [8]. Recent research has expanded to include environmental factors affecting the seismic behavior of squat shear walls. For example, studies by Rong et al. [16] examined the impact of frost damage and exposure to offshore atmospheric environments on these walls, highlighting the need to consider environmental degradation in their seismic design. Similarly, Eid et al. [25] and Tong et al. [26] investigated the impact of construction materials, such as low-performance concrete (LPC) and UHPC, on the shear capacity and overall seismic performance of squat shear walls, finding that LPC can reduce seismic performance while UHPC can enhance it. Advanced analytical and numerical modeling techniques have also contributed to the understanding of squat shear wall behavior. Research by Sivaguru et al. [21] and Hosseini et al. [27] found that openings could significantly weaken the walls’ seismic resistance, emphasizing the need for careful reinforcement detailing around these openings. Environmental factors, such as chloride ion erosion and freeze-thaw cycles, also significantly affect the seismic performance of squat shear walls. Studies by Zheng et al. [23,28–30] and Yang et al. [31] demonstrated that environmental degradation could reduce the seismic capacity of these walls, underscoring the importance of incorporating such factors into the design and maintenance of squat shear walls. Similarly, chemical reactions within the concrete, such as alkali-silica reaction (ASR), can compromise the seismic resilience of these walls [32]. The role of boundary conditions and construction details in the seismic performance of squat shear walls has also been extensively studied. Research by Gulec et al. [15,33] provided insights into how boundary conditions influence shear strength and seismic performance. Different reinforcement materials have been explored for their impact on seismic performance as well. Studies by Yu et al. [18] and Lim et al. [34] found that steel fiber RC (SFRC) and strain-hardening cement composite (SHCC) can enhance shear strength and seismic resilience. The influence of wall geometry has also been a key area of research. Kim et al. [35] found that flanges can enhance seismic performance by providing additional lateral resistance. Yang et al. [36] emphasized the importance of considering geometric details in seismic design. Numerical simulations have become increasingly important in understanding the seismic behavior of squat shear walls. Tariq et al. [20] utilized gene expression programming to estimate the shear strength of RC squat walls, offering a novel approach to predictive modeling in seismic design. Akl et al. [12] conducted a seismic collapse risk assessment of low-aspect-ratio RC shear walls using FEMA P695 methodology, providing valuable insights into the probabilistic assessment of seismic performance. The integration of new materials, such as ultra-high-performance fiber-reinforced concrete (UHPFRC), has also been explored to enhance seismic performance. Nagib et al. [19,37] demonstrated that UHPFRC could significantly improve the seismic resistance and energy dissipation capacity of squat shear walls. Kang et al. [38] effect of cement matrix’s type on the shear performance of lightly reinforced squat shear walls subjected to cyclic loading. Finally, the role of the horizontal reinforcement ratio in improving the seismic performance of BFRP-RC squat shear walls was studied by Miao et al. [39]. Accordingly, the seismic performance of squat RC shear walls is influenced by various factors, Table 1, including material properties, wall geometry, reinforcement detailing, environmental conditions, and loading scenarios. While significant advancements have been made in understanding squat wall behavior, there remain gaps that require further research, particularly concerning the long-term effects of environmental degradation and performance under extreme loading conditions.

Over the past decades, experimental methods have been used as the main approach for investigating the behavior of civil structures [40,41]. In this regard, the failure mechanisms and modes of squat shear walls, which are critical aspects that significantly influence their seismic behavior, have been mainly investigated experimentally at the element level [10,24,31]. In general, squat shear walls, characterized by their relatively short height-to-length ratios, are prone to various failure modes, particularly under seismic loading conditions [42,43]. The failure mechanisms in these walls include shear failure, flexural-shear failure, shear sliding failure, flexural cracking, diagonal cracking, concrete crushing, brittle failure, and ductile failure [44,45]. Each of these mechanisms presents unique challenges that must be addressed to ensure the structural integrity and resilience of squat shear walls during seismic events. Shear failure is one of the most critical failure modes in squat shear walls, characterized by the formation of diagonal cracks and subsequent crushing of concrete, leading to sudden and brittle failure. This failure mode can be prevented by incorporating adequate shear reinforcement, which helps in distributing shear stresses and preventing the initiation and propagation of diagonal cracks [46,47]. As shown in Table 2, the implementation of appropriate shear reinforcement is essential to mitigate this type of failure and enhance the wall’s overall performance under seismic loads. Flexural-shear failure involves the simultaneous occurrence of flexural cracking at the wall’s base and shear cracking along its height, resulting in complex and unpredictable failure patterns. In order to prevent this failure mode, the use of high-strength concrete and well-detailed reinforcement is recommended.

These measures help control both flexural and shear cracks, thereby improving the wall’s resilience against seismic forces [31,43]. Shear sliding failure is another significant concern, where horizontal cracks develop along the plane of maximum shear stress, leading to substantial displacement and potential structural collapse. The incorporation of transverse reinforcement is a key preventive measure for this failure mode, as it helps prevent the propagation of horizontal cracks and subsequent shear sliding [48–50]. Flexural cracking, which primarily occurs at the base of the wall due to bending moments, can severely compromise the wall’s load-bearing capacity. Proper reinforcement detailing at the base is crucial to managing bending moments and preventing the onset of flexural cracking [31,50]. Additionally, diagonal cracking, caused by high shear stresses, poses a significant risk of shear failure if not adequately controlled. The strategic placement of reinforcement and optimization of concrete strength is necessary to control diagonal cracking and ensure the wall’s stability [4,51,52]. Concrete crushing is a localized failure mechanism that occurs at points of high compressive stress, compromising the structural integrity of the wall. Ensuring sufficient concrete cover and maintaining high concrete quality are essential preventive measures against this type of failure [49,53–56]. Therefore, understanding the various failure mechanisms and modes of squat shear walls is essential for improving their seismic performance. By implementing appropriate preventive measures, such as enhanced reinforcement detailing and the use of advanced materials, the resilience of these walls against seismic forces can be significantly improved, ultimately leading to safer and more durable structures.

The seismic behavior of squat RC shear walls is a complex phenomenon influenced by various structural and material parameters. The influence of these parameters has been extensively studied to understand how they affect the overall performance of these walls during seismic events. Concrete strength is one of the most critical factors determining the seismic behavior of squat shear walls. Higher concrete strength increases the load-bearing capacity and reduces crack propagation during seismic events. Table 3 summarizes the influence of material properties on the seismic behavior of squat shear walls. It highlights that higher concrete strength, appropriate reinforcement types, and the addition of steel fibers contribute to improved seismic performance.

Moreover, reinforcement detailing plays a significant role in enhancing energy dissipation and controlling shear deformations, preventing brittle failures. Previously, Ganesan et al. [58] demonstrated that high-performance concrete with added steel fibers significantly enhances the first crack load, overall structural strength, and energy dissipation capacity under lateral cyclic loading. Similarly, UHPC squat shear walls exhibited superior performance in cyclic tests, with increased load-bearing capacity and reduced lateral deformations [6,7]. This aligns with findings from Chen et al. [59] and Chetchotisak et al. [60], who also highlighted the importance of concrete strength in seismic performance.

The application of high-strength concrete is further supported by the work of Liu et al. [43] where experimental and numerical investigations confirmed the enhanced seismic resilience of squat shear walls constructed with high-strength materials. The type of reinforcement used in squat shear walls plays a crucial role in influencing their seismic performance. Different types of reinforcement, such as steel, GFRP, and CFRP, affect the ductility and energy absorption capacity of the walls. Arafa et al. [3] emphasized that GFRP-reinforced squat walls demonstrated effective resistance to lateral loads, and their study highlighted the importance of considering concrete shear contribution and boundary element confinement for accurately predicting the ultimate flexural and shear strengths. Additionally, Woods et al. [46] found that CFRP sheets effectively restored the in-plane strength of earthquake-damaged RC shear walls, significantly enhancing their load-bearing capacity and overall seismic performance. These findings are consistent with those of Fathalla et al. [11], who observed that the type and detailing of reinforcement directly impact the energy dissipation and deformation characteristics of squat shear walls under seismic loads. Steel fibers, when added to concrete, further enhance the seismic performance of squat shear walls. Hosseini et al. [61] examined squat RC shear walls with steel and GFRP rebars. Testing six specimens, they found hybrid reinforcement improved seismic performance by modifying failure modes, enhancing energy dissipation, ductility, and load factors, and delivering superior hysteresis behavior compared to GFRP-only walls. Hybrid rebars proved effective in seismic applications.

Ganesan et al. [58] reported that steel fibers, at a volume fraction of 1% to 2%, increased the load-bearing capacity by approximately 25% and improved energy absorption by 30%. This improvement is attributed to the ability of steel fibers to delay the onset of shear cracking and enhance the ductility of the concrete, which is critical for preventing brittle failures during seismic events. Lim et al. [34] also supported these findings, noting that steel fibers contribute to the overall shear behavior of squat shear walls, particularly in configurations with vertical slits. Reinforcement detailing is another critical parameter that influences the seismic behavior of squat shear walls. Proper detailing, particularly the transverse reinforcement, is essential for controlling shear deformations and preventing brittle failures. Habibi et al. [32] found that a transverse reinforcement ratio of 0.5% to 1% was optimal for controlling shear deformations, thereby enhancing the energy dissipation capacity of the walls during seismic loading. This is consistent with the observations of Jin et al. [42] and Ma et al. [62], who emphasized the importance of reinforcement detailing in ensuring the structural integrity and seismic resilience of squat shear walls. The influence of structural parameters on the seismic performance of squat shear walls is further illustrated in Fig. 5, which shows variations in shear strength with design parameters such as aspect ratio, axial load ratio, boundary reinforcement ratio, and web reinforcement ratio [60]. This figure emphasizes the complex interplay between structural and material parameters in determining the overall seismic performance of squat shear walls, as also highlighted by Devine et al. [53] and Gondia et al. [63]. Additionally, the damage patterns of various squat shear wall materials, as depicted in Fig. 6, underscore the importance of material properties in influencing seismic behavior. Ultra-high-performance concrete and UHPFRC specimens exhibited distinct damage patterns under different shear stress demands, highlighting the role of material composition in determining the extent and nature of damage during seismic events [57]. These observations are corroborated by the experimental findings of Han et al. [4] and Hosseini et al. [27], which further reinforce the importance of understanding material behavior to optimize the seismic design of squat shear walls.

This section reviews the various modeling approaches employed in the literature, encompassing analytical models, numerical simulations, and machine learning techniques, all supported by extensive experimental validations, Tables 4 and 5. The strut-and-tie model is a widely adopted analytical approach for modeling the internal force distribution within squat shear walls. Chetchotisak et al. [60] developed a strut-and-tie model specifically tailored for predicting the shear strength of squat shear walls under earthquake loads, demonstrating its efficacy in capturing the complex force interactions as shown in Fig. 7. Similarly, Kassem [64] proposed a closed-form design formula based on the strut-and-tie model, enhancing the predictive capabilities for shear strength in squat walls. Massone et al. [65] further advanced this approach by modeling squat structural walls controlled by shear, providing a robust framework for shear response estimation. Massone [66] introduced a shear-flexure interaction model calibrated for squat structural walls, offering improved strength predictions by considering the interplay between shear and flexural forces. This approach was validated through experimental data, showcasing its reliability in practical applications. Chen et al. [59] developed an alternative shear strength equation for RC squat walls, emphasizing the importance of ensuring deformation capacity. This equation provides a simplified yet accurate method for estimating shear strength, facilitating easier design processes. Finite element modeling has been extensively utilized to simulate the behavior of structural components over the past [67–69]. In this context, Belletti et al. [70] employed a PARC-CL model to numerically predict the response of squat shear walls subjected to monotonic loading, achieving high accuracy in load-bearing capacity and deformation predictions. Damoni et al. [71,72] utilized nonlinear finite element analyses to simulate crack propagation and the transition from flexural to shear-dominated behavior, aligning closely with experimental observations. Gopalarathnam et al. [73] conducted nonlinear finite element dynamic analyses of squat shear walls with openings, highlighting the influence of openings on seismic performance. Similarly, Jin et al. [42] performed finite element modeling of squat shear walls under combined cyclic and high axial loads, providing insights into their complex loading responses. Liu et al. [43] investigated the seismic performance of RC squat shear walls with single post-openings reinforced by steel plates through both experimental and numerical methods, validating their finite element model results against empirical data. Kolozvari et al. [74] utilized OpenSees’ capabilities for modeling nonlinear behavior in RC walls and columns, with a focus on combined shear and flexural responses. The paper introduced the shear-flexure interaction MVLEM (SFI-MVLEM) and the fixed-strut-angle model (FSAM) to more accurately capture these interactions. Additionally, new material models, ConcreteCM and SteelMPF, improve the representation of cyclic degradation and prevent stress overshooting. Validated against experimental data, these models enhance load capacity and stiffness degradation predictions, particularly for structures with notable shear-flexure interaction. Petrone et al. [75] presented a versatile numerical model capable of nonlinear analysis for squat-to-tall reinforced-concrete shear walls, accommodating a range of loading conditions and wall geometries. This comprehensive framework allows for the simulation of various failure modes and seismic responses. Additionally, Rasoolinejad et al. [76] examined the size effect on squat shear walls using the microplane model M7, providing insights into how scaling influences seismic performance. This is crucial for ensuring that models remain accurate across different wall sizes and configurations.

Machine learning techniques have gained prominence in predicting the properties and behavior of materials and structures [77–81]. In this context, the behavior of various materials [82,83] and structural elements [84–87] has been estimated. Chen et al. [13] utilized a hybrid artificial neural network-particle swarm optimization model to predict shear strength, demonstrating superior accuracy compared to traditional methods. Goh et al. [88] applied multivariate adaptive regression splines (MARS) and neural network models to forecast shear strength, further validating the potential of these approaches in structural engineering. Gondia et al. [63] introduced mechanics-guided genetic programming expressions for shear strength prediction, integrating physical principles with data-driven methodologies. Nguyen et al. [89] used machine learning-based formulations to predict the shear capacity of squat flanged RC walls, offering a novel approach to seismic design. The presence of openings in squat shear walls introduces additional complexities in their seismic performance. Feng et al. [90] developed an interpretable XGBoost-SHAP machine learning model, enhancing the transparency and reliability of shear strength predictions for squat RC walls. Le Nguyen et al. [91] conducted a comparative study of various machine learning approaches for lateral strength estimation of squat shear walls, highlighting their practical implications and effectiveness. Sulaiman et al. [92] examined the efficiency of the XGBoost algorithm for predicting the shear strength of squat RC walls, performing comprehensive parametric analyses to optimize model performance. Nguyen et al. [93] further improved data-driven models for estimating shear capacity, emphasizing enhanced predictive accuracy and robustness, particularly in the case of random forest (RF) and gradient boosting regression tree (GBRT). Finally, Kazemi et al. [94] introduced an advanced ensemble approach for seismic risk and probability assessment by combining multiple machine learning models with optimization techniques. This stacked model integrates algorithms like decision trees, support vector machines, and gradient boosting and utilizes optimization methods, such as Bayesian and genetic algorithms, to refine model choice and parameters for peak performance. Focused specifically on RC shear walls, it analyzes structural and material factors affecting resilience to earthquakes, achieving 99.1% accuracy for incremental dynamic analysis (IDA) and 99.4% for seismic fragility curves. For user convenience, the study includes a graphical interface (GUI) that displays performance levels and seismic curves and calculates mean annual frequency for seismic hazards, providing a practical tool to support improved seismic safety decisions for concrete structures.

Shabana et al. [95] investigated the shear strength of GFRP-RC squat walls using the strut-and-tie model, demonstrating significant improvements in seismic performance. Their study underscores the benefits of advanced reinforcement materials in enhancing the ductility and strength of squat shear walls. In addition to that, Shabana et al. [96] investigated the stiffness characteristics of squat walls reinforced with glass FRP (GFRP) bars method to estimate the post-cracking shear stiffness of squat shear walls. Nagib et al. [19] explored the cyclic behavior of squat RC shear walls strengthened with UHPFRC, showcasing enhanced durability and seismic resilience. This approach highlights the potential of fiber-reinforced materials in modern structural design. Kim et al. [10,56] focused on the shear strength modeling of flanged squat walls, particularly in nuclear power plants, emphasizing the critical role of boundary elements. Their models account for high-strength reinforcing bars and boundary flanges, providing accurate shear strength predictions under seismic loads. Kim et al. [97] investigated flanged squat walls reinforced with 690 MPa bars, and found that Incorporating flanges significantly boost shear strength by 40%. Additionally, high-strength bars perform comparably to conventional ones, and shear strength surpasses ACI 318-19 limits by 200%. Woods et al. [46] utilized image analysis methods in the seismic rehabilitation of squat RC shear walls using CFRP sheets, demonstrating effective strengthening strategies. This work highlights the integration of advanced materials and diagnostic techniques in enhancing structural resilience. Weng et al. [98] focused on predicting the lateral load-displacement curves for RC squat walls failing in shear, providing critical data for understanding their deformation characteristics under seismic loading. Finally, Ocampo-Escobar et al. [99] compared the analytical findings with experimental data to identify important parameters impacting the effective stiffness of RC squat walls. Fig. 8a illustrates the reinforcement of the wall with truss elements, while Fig. 8b shows the wall with brick elements and steel reinforcement embedded into the wall.

Looi et al. [100] developed ultimate drift prediction models for rectangular squat RC shear walls, facilitating better seismic performance assessments. Seif Eldin et al. [101] studied the seismic performance parameters of fully grouted reinforced masonry squat shear walls, while Faraone et al. [51] analyzed damage patterns in both squat and flexural RC shear walls, contributing to a deeper understanding of failure mechanisms. Massone et al. [102] developed a single-panel model for estimating the shear response of squat RC walls, simplifying the analysis while maintaining high predictive accuracy. This approach is particularly useful for preliminary design and assessment purposes. Many studies integrate multiple modeling techniques to enhance prediction accuracy and reliability. For instance, Damoni et al. [71,72] combined finite element methods with discrete element models to capture complex behaviors such as cracking and shear-flexure interactions. Fig. 9 shows the squat RC wall configuration setup, while Fig. 10 demonstrates the verification of the prediction model compared to tested high axial load ratio ALR squat walls.