Vulnerability assessment of sustainable seismic retrofit solutions for reinforced concrete structures: A multi-faceted approach

Abstract

Significant damage to structures has been observed in several major seismic events within the Himalayan region recently, highlighting the need for further investigation into their potential vulnerability. While building codes are frequently improved especially after a huge earthquake disaster, existing structures remain susceptible and should be retrofitted to enhance their performance and decrease vulnerability. This study aims to endorse public safety and well-being by lowering the potential risk of casualties and fatalities resulting from earthquakes effects on existing reinforced concrete (RC) structures, especially in the Himalayan region. The goal is to assess the seismic vulnerability of RC structures and to identify a suitable retrofit solution using a multi-faceted approach, where the impact of the retrofit solution is estimated, based on reducing the seismic vulnerability, retrofit cost, and carbon dioxide (CO₂) emission. A multi-story RC frame structure is a case study built in the seismically prone Himalayan region. Various indicators are employed in this study to evaluate the seismic vulnerability of the building including collapse fragility functions, vulnerability index (VI) based on capacity spectrum method, and other soft-story related parameters such as story shear, inter-story drift, plastic hinge mechanism, damage state, and stress history in soft-story columns, in assessing how seismic retrofitting affects structural performance. Four different retrofitting scenarios are considered to reduce the vulnerability of the existing structure so that the optimized one can be selected based on the proposed multi-faceted approach. This study focuses solely on retrofitting ground story columns, as it is expected to have a minimal economic, social, and environmental impact, making it an easy choice for decision-makers to implement. Finally, the cost-effectiveness is quantified based on the retrofit cost and global warming potential of considered retrofit materials, and the optimization of retrofitting strategies based on the proposed multi-faceted approach, using VI, retrofit cost, and CO₂ emission.

Graphical abstract

Keywords

earthquake / retrofitting / vulnerability / performance / global warming potential / cost

1 Introduction

Human fatalities and economic losses due to natural disasters have significantly increased during the last few decades. Turkey [1,2], New Zealand [3] Nepal [4], Tohoku [5], Christchurch [6], Van [7], Chile [8], Haiti [9], Italy [10], and Kashmir [11] are some of the examples of devastating earthquakes that exposed the vulnerability of existing building infrastructure around the world. In terms of human life losses, there were 46000–316000 casualties reported in Haiti, 20475 fatalities in Tohoku, and 15000 casualties in Kashmir earthquakes. In addition, around 1.108 million and 3.5 million people were left homeless in Tohoku and Kashmir earthquakes. On the other hand, the economic losses in the Tohoku earthquake were 140 billion USD, 5.2 billion USD in the Kashmir earthquake, and 2.2 billion USD in the Van earthquake. Seismic capacity enhancement via retrofitting reduces the potential vulnerability of the structure and consequently decreases the extent of losses after the earthquake [12,13], and therefore, is used to enhance the structural response [14,15]. The retrofitting methods comprise a new lateral load-resisting mechanism or enhance the structural performance of critical elements [16–20]. The structural performance enhancement of critical components can be employed in two ways, one way is to lower the demands on the system or another way is to increase the capacity of the system, attained by enhancing the lateral stiffness, strength, and ductility parameters or by combination of any of them [21–24].

Seismic vulnerability assessment is crucial in identifying the potential risks associated with reinforced concrete (RC) structures. Thus, the seismic vulnerability evaluation of existing structures has become a main interest in developing seismic assessment techniques [25]. Various researchers have employed different approaches to evaluating the vulnerability of RC structures [26], including 1) fragility curves [27–29], which provide a probabilistic measure of the likelihood of damage based on seismic demand parameters like peak ground acceleration, spectral acceleration, etc.; 2) damage probability matrices [30–32], which offer a more detailed assessment of the potential damage states, including cracking, yielding, and collapse, and can be used to evaluate the effectiveness of various retrofit alternatives; and 3) finite element analysis [33–38], which provides a more detailed interpretation of the structural response under seismic loading, including the effects of material nonlinearity, geometric nonlinearity, and can be used to simulate the structural response to different seismic scenarios. All these proposed methods for determining vulnerability can be categorized into two main classes: empirical and analytical. Empirical approaches account for the evaluation of vulnerability by associating earthquake intensity and the damage level (statistical method) [39–50], whereas analytical methods are based on numerical models that replicate the main characteristics of the structure and evaluate the structure’s capacity [51] against the seismic demand due to certain hazard level (quantitative method) [52–67]. Each method has its benefits and constraints, and the selection of approach depends on the explicit context and aims of the study, as well as the available data and computational resources.

Numerous empirical approaches for seismic vulnerability assessment of existing structures have been offered in the past, like one suggested by Thermou and Pantazopoulou [68] for estimating the inter-story drift by linking the stiffness of the structure to the ratio of area of vertical members. The empirical methods mostly depend on basic empirical relationships, which may not predict the complex behavior of RC structures subjected to seismic loading. Therefore, advanced modeling procedures, like nonlinear finite element analysis, can offer a more accurate and comprehensive understanding of seismic vulnerability. El Khoudri et al. [69] used a technique to assess the vulnerability of structure through incremental dynamic analysis (IDA), which is a computationally expensive approach, for the calculation of probable losses owing to an earthquake event. Emami and Halabian [70] worked on developing fragility functions along with the probability of collapse of high-rise RC structures using the IDA and pushover analysis (multi-directional). Similarly, the objective of the study was not on formulating a vulnerability index (VI), but rather on the probabilistic judgment of the collapse via fragility analysis. Marasco et al. [64] compared the assessment of the VI based on nonlinear pushover analysis and revealed that it is faster and easier to be applied, for buildings where the fundamental mode controls the response of structure. Similarly, Blasone et al. [61] tried to reduce the computational time by proposing a 2-D model that accounts for the torsional effects in irregular buildings, Oyguc et al. [62] considered multiple earthquake excitations for irregular structures, and Domaneschi et al. [63] proposed a method for vulnerability assessment that includes an initial building assessment through nondestructive methods, followed by dynamic modal identification for calibrating numerically developed models. Scalvenzi et al. [23] proposed a multi-hazard-based performance assessment of structures to implement various retrofit strategies and evaluated their economic sustainability. Gallo et al. [71–74] have conducted groundbreaking research on seismic retrofit materials, considering various factors to optimize the seismic retrofit solution. He utilized Multi-Criteria Decision-Making (MCDM) to select the best solution while taking into account environmental and economic parameters.

In this study, a VI is proposed to assess the seismic vulnerability of RC structures. Here, the VI is determined by the ratio of the shear force at the performance point to the total base shear of a structure and is a critical metric that can be used in seismic risk assessment and performance-based engineering. This index considers various parameters, including the structure’s properties (such as material properties, and structural system), seismic hazard (defined by the seismic zone), and building code requirements [75]. In the seismic vulnerability assessment of the retrofitted structures, the integration of a VI signifies an important methodological advancement. Under the earthquake loading scenario, this index provides important knowledge about the seismic vulnerability of the structures and can help in assessing the potential damage or collapse of the structure. By quantification of the vulnerability to the seismic forces, practitioners and decision makers can choose risk reduction procedures that assure the reduction in potential vulnerability and enhanced performance of the structure. The advantages of this index over the aforementioned methods are the easiness, and flexibility enough to consider multiple parameters. This quantitative metric not only offers a clear and tangible measure of the seismic performance of the structure but also facilitates informed decision-making by practitioners and decision-makers.

Besides the structural performance, the cost and sustainability related to the retrofit solutions cannot be ignored. Cost comparison and global warming potential (GWP) determination are the vital parameters to be considered in the retrofit optimization [76–86], as they provide complete knowledge of the economic and environmental consequences of retrofit solutions. Accurate cost estimates empower practitioners to thoroughly evaluate the economic viability of specific retrofitting options. This vital information not only enhances the decision-making process but also ensures that the best choices are made for successful outcomes. The retrofit cost varies significantly and depends on the cost of materials, application, maintenance and repair, etc. among others. In the same way, the GWP of these materials varies, for instance, steel possesses a greater GWP because it requires greater energy for production [87]. Similarly, the quantification of carbon footprint and resulting environmental consequences of the retrofit solutions, allow the practitioners to optimize the retrofit solution that offers minimal environmental impact and ensure the global sustainability of the built environment. The integration of cost analysis and GWP estimation into the assessment of retrofit solutions assures a cost-effective and sustainable solution without compromising the safety and strength performance. Thus, fostering a more complete and informed approach for decision making, that includes various parameters to consider for optimization of best-fit solutions. By including both the cost and GWP along with seismic vulnerability analysis, this study identifies the optimal retrofit solution that balances seismic vulnerability with economic and environmental sustainability.

Despite advancements in retrofitting techniques, there remains a need for a holistic approach that considers the impact on the structural performance (e.g., VI or seismic fragility), economic feasibility, and environmental impact of retrofit strategies. Studies, as mentioned above, have emphasized distinct materials or retrofitting solutions, but an inclusive comparison of these solutions is lacking. Moreover, a comprehensive methodology that addresses the three basic parameters of retrofit optimization, i.e., vulnerability, cost, and sustainability, is required. This study addresses this research gap by integrating vulnerability assessment, cost implications, and GWP analysis into the framework.

The current study contributions can be listed as follows.

1) A novel Performance-Level approach that considers various performance levels under seismic loading conditions. It comprises of evaluation of the structural response at different performance levels, by studying the behavior through these performance levels.

2) A sustainability approach that estimates the environmental impact of retrofit solutions, mainly in terms of reduction in carbon dioxide (CO₂) emission.

3) A multi-faceted integration approach that involves the combination of multiple criteria, such as retrofit cost, VI, and GWP factors, to select the best retrofit strategy.

4) A relatively new retrofit material Engineered Cementitious Composite (ECC) is introduced and compared with conventional retrofit materials like Reinforced Concrete Jacketing (RCJ) and Steel Plate Jacketing (SPJ).

This holistic approach ensures that retrofitting decisions are made based on a balanced consideration of various factors, leading to optimal retrofit solutions for existing structures.

2 Multi-faceted framework

The proposed multi-faceted framework consists of two phases as presented in Fig.1, where the first phase focuses more on the structural performance under various retrofit solutions and determining the seismic VI that can be used in many aspects to assess the performance of the structure. The second phase of the framework focuses on the most important parameters that decision-makers want to consider before selecting the optimum retrofit solution i.e., retrofit cost and the environmental impact. Phase I begins by selecting a 5-story hospital building as the structure of interest, along with various retrofitting strategies aimed at enhancing its seismic vulnerability. The first step involves creating nonlinear finite element models for the structure in both pre-retrofit and post-retrofit conditions. Nonlinear pushover analysis is then conducted in the principal orthogonal directions (longitudinal and transverse) of the structure to identify weaknesses in its lateral load-resisting system. During the generation of load-deformation curves, lateral displacements are applied at the top of the structure, and the resulting base shear values are recorded. As the lateral displacement is incrementally increased, components such as columns begin to yield. After yielding, the loads are redistributed along the structure, reflecting the behavior of the structure under seismic loading conditions. This analysis helps in understanding how the structure responds to lateral forces and provides insights into potential failure mechanisms that can inform the selection and implementation of effective retrofitting strategies [88]. Phase II starts by computing the quantities of retrofit materials used in each strategy. It is the most critical step since the cost and CO₂ emission calculation depends merely on the amount of material used. The cost of each retrofit strategy is computed and plotted against the VI for selecting the optimal solution. Also, the CO₂ emission is estimated for each retrofit strategy, and at the end a final comparison between vulnerability, cost, and CO₂ emission is made for a better understanding of the impact of each retrofit solution.

2.1 Numerical modeling details

ETABS V21 [75] is a widely used commercial finite element software specifically designed for the analysis and design of building structures. It offers a range of analysis capabilities including time history analysis, response spectrum analysis, modal analysis, pushover analysis, and gravity load analysis. The software provides material models that accurately capture the nonlinear behavior of various materials such as concrete, steel, rebars, tendons, etc., under uni-directional and cyclic loading conditions. Users also have the flexibility to define custom material models to meet specific requirements.

Given that the nonlinear material behavior significantly influences the structural response, precise modeling of constitutive relationships (stress–strain cyclic response) is crucial. ETABS V21 allows for the consideration of geometric nonlinearities (linear, nonlinear, P–Δ effects) and various loading conditions (static or dynamic). The software features a rigid diaphragm slab option to ensure axial stiffness and uniform distribution of lateral displacements across all columns at the same story level. In ETABS V21, structural members such as beams and columns are modeled using distributed plasticity. For lateral load analysis, lumped plasticity or concentrated plasticity in the form of plastic hinges is employed to simulate the flexural behavior of the lateral load-resisting system. The length of a plastic hinge can be defined by the user, offering options for both relative and absolute member lengths. The software provides a user-friendly interface for defining and analyzing structural behavior, making it a valuable tool for assessing and enhancing the seismic performance of building structures.

2.2 Nonlinear pushover analysis

The nonlinear pushover analysis method is utilized to assess the actual/ultimate strength and seismic response of a structure. This analysis involves gradually increasing lateral load/displacement while considering applied gravity loadings. Key parameters such as yielding, cracking, formation of plastic hinges, level of damages, story shears, inter-story drifts, and failure modes of the structure are computed during the analysis. The capacity curve for the structure is generated by plotting the total base shear against the total roof displacement (Fig.2). This curve provides a target displacement corresponding to that induced by the design earthquake. The nonlinear pushover analysis accounts for structural failure and can be used to evaluate collapse load and ductility capacity.

Standards such as FEMA-356 [89] and ATC-40 [90] have defined modeling limitations, acceptance criteria, and pushover analysis methods. Pushover analysis can be conducted in either load-controlled or deformation-controlled environments. In the latter, the structure’s response is governed by deformation, allowing for the computation of post-peak behavior even after reaching peak load. This post-peak behavior is crucial in earthquake engineering studies for determining performance levels, displacement ductility, response modification factors, and other important parameters.

In this study, a displacement-controlled nonlinear pushover analysis procedure is adopted to simplify and streamline the assessment of structural response. This approach provides a straightforward and computationally efficient method for evaluating the behavior of the structure under seismic loading conditions.

After setting up the material models, geometric nonlinearities, assigned loadings, meshing details, and analysis type in the ETABS model, the next step involved defining boundary conditions for the structure. To validate the model, the results were cross-checked using SeismoBuild [91], another commercially available software. The material models and modeling assumptions were kept consistent between the two software packages, ensuring a reliable comparison. Once the model was validated, the analysis was executed on the reference model in ETABS. Important parameters such as the capacity curve, inter-story drift, story shear, plastic hinge details, moment-curvature behavior, and others were calculated and plotted according to industry standards. Subsequently, the model underwent retrofitting, focusing solely on the ground floor columns. Various retrofitting strategies were implemented as outlined earlier. While maintaining the same parameters as the reference structure, the analysis was conducted for each retrofitting option. The results were recorded and plotted against the reference structure’s data to evaluate the effectiveness of retrofitting only the ground story columns on the overall structural response. This comparative analysis aimed to assess how the different retrofitting strategies impacted the global behavior of the structure, particularly focusing on the ground floor columns.

2.3 Structural performance evaluation

Given that the soft-story mechanism plays a vital role in our assessment approach and was identified in the preliminary analysis of the reference structure, it is imperative to thoroughly investigate the parameters influencing the structure’s performance, particularly concerning story response. In this way, it will be very easy to quantify the retrofit impact, on the overall performance of the structure. In addition to that, since this study merely focuses on retrofitting the soft story only (in this case ground floor, as evident from the analysis), thus it becomes very important to study the parameters that help us understand the story response to completely understand the structural performance. Therefore, in this section, various parameters will be described briefly that are considered in this study to assess the story response and individual column response. An illustration of the mechanism is also presented in Fig.3. In this way, the retrofitting impact on the global performance of the whole structure, on individual story response, and most importantly on the localized column behavior can be studied. The parameters studied are presented in the following section.

2.3.1 Story shear and drifts, plastic hinges, moment curvature relation, stress history in columns, and collapse fragility functions

Story shear comprehends the cumulative lateral forces calculated at definite levels above the considered story. It refers to the distribution of lateral forces on a structure at different stories and is transferred laterally from one level to another due to wind or seismic forces. Story drift refers to the lateral displacement of one story in a building relative to another story above it divided by the height of that story, due to lateral loads like wind or seismic forces on the structure. It is an important parameter in structural design as excessive drift beyond code-specified limits can lead to damage or even failure.

Plastic hinge (PH) represents the behavior of a member (e.g., the column in this case) when it endures plastic deformation and is used to model the nonlinear behavior of that member, where plastic deformation occurs due to seismic events. ETABS allows for definition and analysis of PHs in structural elements to precisely consider the nonlinear behavior of the member. By incorporating PHs in the analysis, the structural response of the building can be assessed and the capacity of the structure to withstand plastic deformations without failure can be evaluated. PHs are usually defined at locations where they are expected to form in the members. PHs are categorized by properties such as yield strength, ultimate strength, and ductility, in addition to various performance levels and damage states (explained in the next paragraph), which define the material behavior during plastic deformation. During nonlinear pushover analysis, due to the application of lateral loads on a structure, when a structural member experiences great deformations in the plastic phase, it is supposed that the whole deformation concentrates at one point referred to as ‘plastic hinge’. Fig.2 presents the five points marked as A, B, C, D, and E to describe the load-deformation response of plastic hinges. Point A presents the start of the load, point B depicts the yielding, and point C is the ultimate capacity however points D and E represent the residual strength and displacement function. Apart from these five points, three more points marked as immediate occupancy (IO), life safety (LS), and collapse prevention (CP) are defined as the acceptance criteria for the plastic hinge following FEMA [92] and ATC 40 [90].

IO refers to very light damage to the whole structure. Moreover, the performance of the structure in terms of its strength and stiffness remains the same as in pre-earthquake conditions. Nonstructural elements along with electrical and mechanical equipment remain safe as well. LS level is considered with 1) significant damage to both structural and nonstructural components, 2) considerable loss of structure’s strength and stiffness as compared to pre-earthquake conditions, and 3) nonstructural components are not in the state of falling hazard. During the CP level, the lateral-load resisting system suffers significant damage as compared to the pre-earthquake strength and stiffness and the structure is on the verge of collapse.

The moment−curvature relationship is an essential concept to describe the relationship between the applied moment (bending moment) and the resulting curvature (rotation) of a structural member, such as a beam or column. It is very important to understand the behavior of structural members, particularly in the nonlinear range where the material may experience plastic deformations [93]. It is typically represented graphically, depicting how the curvature of a member changes with the applied moment. In the elastic range, the relationship is straightforward, following Hooke’s Law. However, in the inelastic range, the relationship becomes nonlinear and more complex as the material undergoes plastic deformations and the stiffness of the member changes.

The stress history in columns reveals the change in stress levels within a column, in response to applied lateral load on the structure. This analysis is significant for evaluating the performance of the column under seismic loadings. Since the columns govern the lateral load-resisting system of these structures, it is therefore very important to understand the column response to ensure the safety of the structure.

Collapse fragility functions are used to predict the probability of potential collapse a structure may experience under changed levels of seismic demand. These functions consider various factors to determine how vulnerable a specific structure is to potential collapse during an earthquake. By using collapse fragility functions, the potential risks associated with a structure can be better studied and mitigation strategies can be applied in the design and construction practices. Several approaches can be used to create fragility functions like empirical data analysis, analytical modeling, probabilistic risk assessment, etc., using which the researchers can construct fragility functions that provide a comprehensive assessment of the vulnerability of the structure to seismic events. However, the current study uses a more comprehensive and globally acceptable method proposed by Vamvatsikos and Allin Cornell [94] and later on adopted by PEER PBEE [95] in their methodology, for constructing collapse fragility functions is a widely used approach in seismic risk analysis. This method is based on the concept of IDA and is designed to estimate the probability of structural collapse under different levels of ground shaking. The simplicity of the method lies in its implementation, where a nonlinear pushover analysis can be used to obtain the collapse fragility function using this method.

2.4 Seismic vulnerability index

In this study, a VI is used to assess the seismic vulnerability of RC structures. This index takes into account various parameters, like 1) structural characteristics, such as building height, material properties (e.g., concrete strength, steel yield strength), and structural system (e.g., moment-resisting frame, shear wall); 2) seismic hazard, defined by the seismic zone and soil type, which affects the seismic intensity and frequency content of the ground motion; 3) building code requirements, including design standards and retrofitting guidelines, and 4) structural detailing, including the presence of seismic detailing, such as hooks and anchors. The VI is calculated using a weighted sum of these parameters, providing a comprehensive and quantitative measure of seismic vulnerability. The significance of this index lies in its ability to provide a simple, yet effective, tool for comparing the seismic vulnerability of different RC structures and evaluating the effectiveness of various retrofitting strategies.

To determine the seismic VI of the reference structures and the retrofitting alternatives the methodology opted for involved the determination of the maximum base shear obtained from the capacity curve and performance point obtained from the intersection of the capacity curve with the demand response spectrum. Many factors affect the seismic vulnerability of existing structures like age, maintenance level, construction materials, location, and soil condition of the structure along with the hazard levels, etc. The capacity spectrum analysis method is employed to determine the performance point of the structure. This performance point is then used to determine the VI of the structure (ζ_E) which is defined as the ratio of the highest tolerable seismic response of the existing structure to the one required for designing a new structure on that site with the identical dynamic properties.

The VI used in this study is based on the nonlinear pushover analysis, which is computed in Eq. (1):

(1){\zeta }_{\mathrm{E}}= \frac{F_{\mathrm{m}\mathrm{a}\mathrm{x}}^{\ast }}{F_{\mathrm{c}\mathrm{o}\mathrm{l}\mathrm{l}\mathrm{a}\mathrm{p}\mathrm{s}\mathrm{e}}^{\ast }},

where F_{\mathrm{m}\mathrm{a}\mathrm{x}}^{\ast } is the value obtained from the performance point of the structure. (Fig. A2 in Electronic Supplementary Material), F_{\mathrm{c}\mathrm{o}\mathrm{l}\mathrm{l}\mathrm{a}\mathrm{p}\mathrm{s}\mathrm{e}}^{\ast } is the max base shear obtained via pushover analyses.

By analyzing the capacity curve alongside the demand spectrum in acceleration–displacement response spectrum (ADRS) format, we can effectively pinpoint the performance point. F_{max}^{\ast } signifies the force corresponding to this performance, while F_{\mathrm{c}\mathrm{o}\mathrm{l}\mathrm{l}\mathrm{a}\mathrm{p}\mathrm{s}\mathrm{e}}^{\ast } denotes the maximum base shear that the building can endure, as calculated through pushover analyses. F_{\mathrm{c}\mathrm{o}\mathrm{l}\mathrm{l}\mathrm{a}\mathrm{p}\mathrm{s}\mathrm{e}}^{\ast } indicates the maximum base shear that the structure can support. Conversely, the F_{max}^{\ast } value can be determined using methods detailed in NTC2018, such as the Capacity-Spectrum Method or the N2 Method outlined in Eurocode 8, ensuring a comprehensive assessment of the structure’s performance under various conditions.

ASCE 7-10 [96] was employed to define the seismic demand in the form of elastic response spectrum for soil class B, Long Period of 8, and damping ratio of 0.05. The default values of S_s and S₁ of 1g and 0.4g were used, respectively. The capacity curve was converted into a bilinear idealized curve using the FEMA 440 [92] equivalent linearization method.

3 Economic analysis

Economic analysis for retrofit solutions can play a conclusive role in solving the social and economic issues of seismic retrofit on stakeholders. It can assist stakeholders in assessing the economic appropriateness of retrofit solutions and their potential costs, by quantifying the costs and their comparison among the options. It can facilitate stakeholders to choose appropriate retrofit methods by relating the costs with the explicit retrofit option. By associating the costs with possible benefits (i.e., income of the stakeholders, funding sources, etc.), decision-makers can identify cost-effective solutions that guarantee the maximum benefits with minimal costs. In summary, the economic analysis for retrofit solutions can offer a methodical and effective base for studying the economic effects of seismic retrofit, facilitating decision-making processes, and endorsing cost-effective solutions.

4 Global warming potential

GWP is a very important parameter to consider in all projects nowadays. GWP quantifies the potential for a given material to contribute to global warming over a specified time horizon and it can have various indicators including CO₂ emission. CO₂ emissions refer to the amount of CO₂ released into the atmosphere during the manufacturing, transportation, and installation of materials used in the retrofitting process. However, only the manufacturing-associated CO₂ emission is considered in this study. Performing an analysis of GWP in structural retrofitting projects is crucial for several reasons, e.g., environmental impact assessment, sustainable design considerations, life cycle assessment, regulatory compliance, and as a decision-making tool. In general, performing an assessment of GWP in retrofitting plans is vital for endorsing sustainable design practices, meeting regulatory needs, and making informed decisions that lessen the environmental impact of structural retrofitting strategies.

5 Case study

5.1 Building model and retrofitting strategies

The structure chosen for this purpose is a five-story building made of RC, with a height of approximately 65 feet. The numerical model for the building is shown in Fig.4 and the building’s layout is depicted in Fig. A1 in Electronic Supplementary Material. The hospital building is divided into six blocks with extension or seismic joints separating them. Each block is designed to act independently under gravity and lateral forces. Therefore, only one block (highlighted in the Fig.4) is modeled and analyzed to represent the entire building, as the data used is similar for all blocks. The building is designed according to seismic codes that were in effect during the project’s execution, with UBC-97 used for lateral load design. The modeling considers geometric and material nonlinearities, with a concrete strength of 4000 psi and steel yield strength of 60000 psi being assumed, the detailed mechanical properties of these materials are provided in Table A1 in Electronic Supplementary Material. Infill walls are very important to incorporate into the numerical model as their presence affects the overall behavior of the structure [97–99]. Therefore, a limitation of the current study is that the impact of infill walls on the lateral load behavior and overall structural performance is not considered. However, given the necessity for open spaces on the ground floor, the amount of infill in that area will be limited compared to the upper floors. This condition will also contribute to a soft story effect on the ground floor due to its reduced lateral stiffness relative to the other levels. Moreover, due to various complexities, and the variations associated with the material of infill walls used in various parts of the world, it was decided not to model the infill elements, an approach that is also adopted by various other researchers [13,26,27,64,100–104].

ASCE/SEI-41-13, Tables 4.2 and 4.3 [105] are mainly used for the recommendation of the material assumptions. Four retrofitting techniques, SPJ, SAJ, RCJ, and ECJ, are being examined to improve the structure’s performance. The retrofitted columns on the ground floor, utilizing all four retrofitting methods (RCJ, SPJ, SAJ, and ECJ), are illustrated in Fig.5. Detailed analysis of various parameters is being conducted for these retrofitting options to determine the most effective solution. In RCJ and ECJ alternatives, the thickness of the jacket is varied, whereas in SPJ, the thickness of steel plates/jackets is investigated. For the SAJ alternative, several angle sizes available in AISC14 [106] were examined with many thicknesses. Tab.1 provides a comprehensive overview of the parameters considered for the four retrofitting strategies. These strategies involve modifications to the current lateral force-resisting system, specifically targeting the columns on the ground floor. The enhancement of the cross sections is based on the recommendations outlined in FEMA-547 [107] and ASCE/SEI-41-13 [105]. These guidelines emphasize detailing approaches, construction methods, and seismic assessment of existing structures. A total of 21 models are created, comprising the original structure without any retrofitting and 20 models for various retrofitting scenarios (five alternatives for each option, as detailed in Tab.1).

The finite element models are developed using the software ‘ETABS V21.2’ [75], with material models for rebars, concrete, and steel being taken from the software’s library. A distinct material model for ECC material is defined based on the research by Gencturk and Elnashai [108]. The material models employed for steel, concrete, rebars, and ECC are depicted in Fig.6.

5.2 Nonlinear pushover analysis

Nonlinear pushover analysis was carried out by applying lateral deformation at the top of the structure and recording the resulting base shear for each corresponding deformation. This process indicates structural deformation in the fundamental mode and calculates the response parameters post-yielding, as a deformation-controlled environment was utilized. The load−deformation curve of the structure provides data on the initial stiffness, ultimate strength, and ductility, enabling the assessment of the structure’s performance and the effectiveness of the chosen retrofitting strategy, as described by Elkady and Lignos [109].

Fig.7 presents the load−deformation curve of the reference model in both the principal orthogonal direction. In the same way, the load−deformation response for the models with retrofit strategies was determined, which offers significant details regarding the stiffness, ductility, and ultimate strength of the building. Fig.8 provides the details obtained from load–deformation curves of all retrofitted models and plotted against the reference model for better understanding. It should be noted that in Fig.8, D_y and P_y are yield displacement and yield load and correspond to the point where the structure starts yielding, hence both values present the same point on the capacity curve. Similarly, D_u and P_u present the ultimate displacement and ultimate loads, the structure possesses. However, it should be noted that the D_u may not necessarily be the point where P_u occurs, and in most cases, the P_u occurs at a displacement lesser than the D_u. In addition to that, the D_y and P_y also present the initial stiffness of the structure and hence, presented in Fig.9 for all the considered models. Overall, it can be inferred that all retrofitting options significantly improved the structural performance, particularly considering that retrofitting was solely implemented at the ground floor columns. This outcome is particularly noteworthy as the cost of retrofitting applications is minimal. Fig.8 that the yield- and ultimate- displacement are not much affected by retrofitting particularly for the cases of RCJ and ECJ alternatives, however, retrofitting enhances the yield- and ultimate- loads considerably. The strength enhancement results for the different retrofitting alternatives are discussed for ultimate strength only. For the SPJ alternative, the ultimate strength increased by 55.9%, 65.3%, 84.7%, 103.1%, and 105.8% for SPJ1, SPJ2, SPJ3, SPJ4, and SPJ5, respectively. In the case of the SAJ alternative, the ultimate strength increased by 68.7%, 83.1%, 63.4%, 72.1%, and 80.2% for SAJ1, SAJ2, SAJ3, SAJ4, and SAJ5, respectively. For the RCJ alternative, the ultimate strength increased by 57.7%, 66.2%, 73.1%, 80.0%, and 86.2% for RCJ1, RCJ2, RCJ3, RCJ4, and RCJ5, respectively. In the case of the ECJ alternative, the ultimate strength increased by 39.6%, 49.2%, 57.8%, 66.3%, and 74.3% for ECJ1, ECJ2, ECJ3, ECJ4, and ECJ5, respectively. Comparing the results, it can be observed that different retrofitting alternatives offer varying degrees of strength enhancement, with each alternative showing distinct performance characteristics.

Apart from the ultimate strength, certain other important parameters can also be evaluated from the capacity curves, i.e., ductility (or lateral drift or displacement) enhancement, effect on the stiffness of the structure, etc. These parameters are plotted separately and presented in Fig.10 in terms of % enhancement in case of ductility and % reduction in terms of time period (or it can be said that the % enhancement in the stiffness of the structure). It should be noted here that the ductility presented here should not be mixed with displacement ductility which is normally evaluated as the ratio of ultimate displacement to the yield displacement. In this study, the enhanced ductility is evaluated in three steps, by finding the difference of ultimate displacement w.r.t yield displacement for all the considered models as the first step, then in the second step for each retrofitting option the value obtained in the first step is subtracted by the value of reference structure, and in third step the value obtained in second step for each retrofitting alternative id divided by the value of reference building obtained in first step and multiplied with 100 to get in percentage.

The same procedure was adopted to find the enhancement in lateral stiffness of the structure and later it was attributed to the time period of the structure. Fig.10 clearly shows that the ductility enhanced by SPJ alternatives, especially SPJ4 and SPJ5 is better than other options. Nevertheless, all the retrofitting options contribute to the enhancement in ductility of the structure or it can be said that the lateral drift or displacement capacity of the structure has been improved by about 60% for all the retrofitting alternatives as compared to the reference structure by just retrofitting the ground story columns. Similarly, these retrofitting strategies are making the structure stiffer thus reducing the time period and increasing the frequency of the structure.

The maximum effect on stiffness is obtained by RCJ and ECJ options while the SAJ option lies within the RCJ2 and RCJ4 values. The least impact on structural stiffness and hence the time period was seen in the case of the SPJ alternative and hence with maximum strength enhancement, maximum ductility enhancement, and minimum stiffness enhancement, the SPJ option stands tall among the others in the first part of the assessment of results.

5.3 Retrofitting impact on structure’s performance

To assess the impact of retrofitting alternatives on the seismic performance of the structures, a detailed assessment was performed to check the various parameters of the structure to strengthen the findings of Subsection 5.2 and narrow down the list of retrofitting alternatives. So, the most suitable options should be considered in the next phase of assessment, i.e., seismic risk assessment. The following sections will discuss the findings in detail.

5.3.1 Story shear

The analysis of Fig.11, in conjunction with Fig.8, reveals significant findings. First, the story shear values increased by the same amount for all stories above the retrofitted story, irrespective of the retrofitting method employed. This indicates that strengthening the ground floor columns not only enhances the load distribution but also results in the upper stories bearing more load and utilizing their capacity. Consequently, this overall strengthening of the structure reduces its vulnerability to seismic loads. Secondly, the percentage enhancement in story shear is consistent across all stories. For instance, if the story shear of the first story is doubled with SPJ-5, a similar doubling of story shear is observed for all other stories. This consistent response pattern is observed across all retrofitting alternatives, highlighting the uniform impact of the retrofitting strategies on the distribution of loads within the structure.

Thirdly, the ultimate lateral load and story shear values exhibit consistent enhancement percentages across most retrofitting options, except for SPJ-1, where the ultimate lateral load increases by 56% and story shear for all stories by 45%. Subsequent SPJ retrofitting options show enhancements of 65%, 84%, 102%, and 105% for SPJ-2, SPJ-3, SPJ-4, and SPJ-5, respectively. Similarly, SAJ-1, SAJ-2, SAJ-3, SAJ-4, and SAJ-5 demonstrate enhancements of 68%, 82%, 63%, 71%, and 79% in ultimate lateral load and story shear. For RCJ-1, RCJ-2, RCJ-3, RCJ-4, and RCJ-5, enhancements are 58%, 66%, 73%, 80%, and 86%, respectively. In ECJ-1, ECJ-2, ECJ-3, ECJ-4, and ECJ-5, enhancements are 40%, 49%, 58%, 66%, and 74%. Fourthly, the maximum enhancement in ultimate lateral load and story shear is observed in SPJ retrofitting, with SPJ-5 showing the highest increase at 105%. SAJ, RCJ, and ECJ retrofitting options exhibit maximum enhancements of 82%, 86%, and 74%, respectively.

5.3.2 Story drifts

Fig.12 and Fig.13 present the total lateral drift of the structure (story-wise) and the inter-story drift of each story, respectively. As previously discussed, one of the objectives of this study is to determine the seismic loss assessment due to the seismic hazard and therefore it is rather important to have an idea about the lateral drift since various non-structural elements in the building are drift-sensitive and their fragility curves are based on the drift. So, to avoid the failure of those non-structural components the inter-story drift should not exceed the threshold limit of the component’s fragility function. Various results can be drawn from these figures. First, it can be concluded from both figures that retrofitting enhances the ductility of the structure and provides more drift on the first floor as well as for all the floors above. The results of these two figures if coupled with the results of Fig.11 give a very clear picture in terms of lateral load capacity and ductility enhancement, that by just retrofitting the columns of the ground floor, the performance of all the above floors also enhanced both in terms of story shear and inter-story drift (in terms of ductility, since the displacement capacity is enhanced).

However, as discussed previously this increase in inter-story drift should be studied in comparison with the fragility functions of drift-sensitive components and the design of those drift-sensitive components should be by the enhanced inter-story drift values. Second, the inter-story drift for SPJ-5 particularly is different than all the other retrofitting options, where the columns of the second story experience much larger drifts as compared to the other options, and the drift values for the second story are even greater than the first story drift.

5.3.3 Plastic hinges

Fig.14 presents the plastic hinge distribution in the transverse direction of the structure. The plastic hinges are referred to as material inelasticity, where the structural elements are modeled with lumped plasticity at the face of the beam in terms of moment M3 only, while the interaction of axial load and biaxial moment (P-M2-M3) is described for the columns. The limit states different plastic hinges reached is also obvious from Fig.14, thus showing the performance levels as IO, LS, and CP as per FEMA 356. The results signify that the plastic hinge formation is done only in the columns, however, no hinges appeared in the beams. It can be seen very clearly that for the reference building, all the damage is focused on ground floor columns hence confirming the soft-story formation mechanism. Also, the ground story yields the highest inter-story drift as also evident from Fig.13 and these results confirmed the reaching of plastic hinges of ground story columns to collapse level thus confirming the formation of soft-story mechanism due to the absence of shear walls or any other arrangement to make the story stiffer.

However, after the application of retrofitting alternatives, the damage levels as well as the distribution of hinges in the 1st story columns changed and the overall performance of the structure was enhanced. By comparing the results of Fig.14, it can be very clearly seen that in reference (un-retrofitted) structure, all the damages are concentrated on the ground floor which can be evident from the inter-story drift of 1st story as well as the formation of hinges only in the ground floor columns and the collapse level of damage in these plastic hinges. Retrofitting the columns of the ground floor with various alternatives enhances the state of damage in some cases by bringing the damage level from collapse to CP while in other cases to LS and even to IO levels. In the case of RCJ and ECJ alternatives, some columns possess collapse level damage while other shows IO or LS levels thus eliminating the chance of damage focusing on a single story and causing the redistribution of damages to the stories above. However, in the case of SPJ and SAJ, a further enhanced response is observed, where the plastic hinges are formed in the second story columns as well thus causing the columns of the above story to yield. Further details could also be obtained from these results.

5.3.4 Moment–curvature relation

To get further detailed information about the state of stresses in the plastic hinges, column 3 (shown on the plan in Fig. A1 in Electronic Supplementary Material) of the ground floor was selected to compute the moment−curvature function and the history of stresses and are presented in Fig.15 and Fig.16, respectively. Two types of results can be very easily drawn from Fig.15. First, it clearly shows that the column’s moment capacity of reference structure is less than any of the retrofitting alternatives considered. Thus, by applying the retrofitting, the moment carrying capacity of the columns is enhanced therefore increasing the total resistance of the structure to lateral loads. Secondly, in the case of SPJ and SAJ alternatives, the curvature values of the reference structure are greater than all the options considered (SPJ1–SPJ5 and SAJ1–SAJ5) for these two strategies. However, in the case of RCJ and ECJ alternatives, the curvature values of the reference structure are less than that of the retrofitted options (i.e., RCJ1–RCJ5 and ECJ1–ECJ5).

5.3.5 Stress history in columns

Fig.16 presents even more interesting results as it compares the state of stress in the plastic hinge with the capacity of the structure when subjected to lateral load incrementally. It can be seen that for reference structure, the column yields at a moment capacity of around 300 k-ft when the capacity of the structure (un-retrofitted) is around 750 kips, however, the column reaches the ultimate capacity of around 330 k-ft when the structure reaches a total capacity of around 992 kips. By performing the retrofitting strategies, the moment capacity of the column is enhanced considerably, and thus the total capacity of the structure is also enhanced accordingly. In the case of the SPJ alternative, a maximum capacity of the column is observed around 800 k-ft which is greater than all the other alternatives. Similarly, in the case of SAJ, RCJ, and ECJ alternatives the maximum capacity of the columns is around 650, 600, and 575 k-ft, respectively. Thus, increasing the capacity of the structure accordingly as discussed in Subsubsection 5.1. Further details regarding the yielding of columns with any particular type of retrofitting option and the corresponding capacity of the structure can be obtained from Fig.16.

5.3.6 Collapse fragility function

The results, in the form of load−deformation curves, are imported into the SPO2IDA tool [95] for analysis. This tool fits the curves by defining four control points and estimates the resulting median for collapse fragility functions. These fragility functions are generated for all scenarios using a dispersion of 0.6 [95]. By creating fragility curves, the vulnerability assessment in terms of the probability of collapse occurrence in each condition becomes straightforward, allowing for comparison among the retrofitting options and with the reference structure. The fragility functions plotted in this study depict the probability of collapse against intensity measures such as spectral acceleration. Fig.17 illustrates the collapse fragilities resulting from this analysis. The findings indicate that SPJ, SAJ, and RCJ retrofitting options significantly reduce the potential for collapse. In contrast, the ECC retrofitting solution shows a relatively lower decrease in potential collapse. It is important to note that the ECC retrofitting considered in this study does not include any reinforcement (i.e., no longitudinal or transverse steel is used), leading to significant cost savings. Nonetheless, all retrofit strategies show a decrease in potential collapse risk.

Fragility functions also strengthen the findings of Subsection 5.3, where the SPJ alternative offers superior performance in terms of reducing the potential collapse as compared to the other retrofitting alternatives. Thus, making the SPJ is the best alternative in terms of making the structure least vulnerable as compared to the other retrofitting options followed by SAJ, RCJ, and ECJ which perform more or less in the same manner and reduce the potential collapse up to the same amount. Retrofitting decreases the damage, and hence enhances the performance of the structure. The enhancement in seismic performance (in terms of reduction in the probability of collapse) for ECC intervention is less as compared to the other strategies, but it is because the ECC jacketing assumed in this study is without any longitudinal and transverse reinforcement, thus the cost comparison might make it more feasible and useful as compared to the other alternatives but the considered performance was less in this scenario, whereas substantial enhancement is noted for the SPJ, SAJ, and RCJ retrofit alternatives.

5.4 Vulnerability index

As mentioned in Subsection 2.4, the VI can be computed once the capacity curve is plotted by obtaining the maximum base share and dividing it by the performance point which can be obtained by selecting a design elastic spectrum (Eq. (1)) [110].

Equation (1) is used to compute the VI, and Tab.2–Tab.5 presents the detailed values of maximum base shear, performance points, and the related vulnerability indices for all the retrofitting alternatives with all the considered options among each alternative. Figure A2 in Electronic Supplementary Material presents the design response spectrum to compute the demand on structure along with the capacity curve and other parameters included for the determination of the performance points for each considered model. Once the performance points are generated, various details can be obtained for instance F_{max}^{\ast } is used in this study for determining the VI. The higher value of the VI indicates the structure to be less vulnerable and vice versa. The results revealed that retrofitting the columns of the ground story only has a considerable impact on the vulnerability reduction of the structure. The VI computed for the reference structure is 0.89. Among the four proposed retrofitting alternatives the SPJ alternative performs relatively well followed by RCJ and ECJ, respectively. However, the SAJ alternative gives the least performance in terms of computed vulnerability indices. The mean vulnerability indices for SPJ, SAJ, RCJ, and ECJ alternatives are computed as 0.69, 0.79, 0.73, and 0.74, respectively. Nevertheless, all the retrofitting alternatives offer better performance in terms of VI as compared to the reference structure. The results revealed by vulnerability indices are coherent with the plastic hinges distribution results presented in Fig.14 and will be discussed in detail in the subsequent section, where a soft-story mechanism is perceived on the ground floor in the case of the reference structure. Based on the VI study, it can be concluded that although all the retrofitting options have enhanced the vulnerability resistance of the structure, still SAJ-3 particularly shows very weak performance in terms of reducing the VI and it is almost similar to the reference un-retrofitted structure. Although SAJ-1 and SAJ-4 also show very little improvement in the VI and can be carefully assessed before opting for a retrofitting option.

To quantify the response of the structure in terms of vulnerability to damage and ductility of the structure, the VI is plotted against the total roof drift. The resulting graph will indicate the structure’s vulnerability on the vertical axis and its ductility on the horizontal axis. Since the VI is obtained by dividing the strength value obtained from the performance point by that of the maximum base shear value, therefore it is a direct indicator of the structure’s strength. On the other hand, the total roof drift indicates the ductility of the structure. It should also be noted that the demand for each case is different and depends on the performance point, therefore in case of increased capacity of the structure, the demand also increases as the capacity curve intersects the demand response spectrum at a higher point. The higher the value on the vertical axis, the more vulnerable the structure will be, and the higher value on the horizontal axis indicates the greater ductility of the structure. Thus, the retrofitting effect on the structure’s VI and ductility can be computed to select the desired option that fulfills the requirements.

Fig.18 presents the graphs of VI vs total roof drift for SPJ, SAJ, RCJ, and ECJ retrofit alternatives. By studying these figures, it is clear that seismic retrofit reduces the vulnerability of the structure and enhances its ductility thus enhancing the performance of the structure. The ductility enhancement is maximum in the case of SPJ4 (Fig.18(a)), which depicts the least vulnerability following SPJ1. Generally, the SPJ alternative presents a very good distribution of results and gives a clear indication of the effect of steel plate thickness on the performance of the structure. Fig.18(b) shows the performance of the SAJ alternative, as the less effective as compared to the SPJ alternative in terms of both vulnerability and ductility. The ductility range of the SAJ alternative lies between 0.045 and 0.05 as compared to the SPJ alternative, where the range was 0.045 to 0.065. On the other hand, the VI also indicates the SAJ alternative to be more vulnerable as compared to the SPJ alternative. Fig.18(c) and Fig.18(d) present even more interesting results, where all the options of RCJ and ECJ alternatives possess more or less similar kinds of performance. Hence the decision makers could easily assess the jacket’s influence on the performance of the retrofit. Thus a 1.5 in ECJ and RCJ are giving almost the same performance as a 3.5 in ECJ and RCJ options. Although the vulnerability is reduced a little bit, overall, all the options for the same retrofit alternative give similar performance in these two cases.

6 Economic analysis

To decide the best retrofitting strategy, the mechanical properties, and vulnerability parameters are not the only criteria decision makers look for. Indeed, one of the most important parameters in deciding the retrofitting strategy will be the retrofit cost. However, the indirect costs (e.g., maintenance cost, resistance to fire, etc.) are also very important to consider, but analysis of those parameters is time-dependent and hence not considered here. To compute the installation costs of each retrofitting option, the rates from the local Pakistani market were used [111], and the results were then converted into USD for a global understanding of the cost impact. To calculate the cost of concrete and steel in RC jacketing along with all allied services, and the cost of steel plate in SP jacketing along with welding and allied services, MRS-2022 [111] was utilized directly. It is important to note that the analysis was conducted in 2024, taking into account the inflation rate while referencing MRS-2022. However, the cost of steel angles demanded a mixed approach where details from MRS-2022 [111] were used in combination with some rates from the industry as well. In the case of ECC, the cost of material is estimated from the study done by Pan et al. [112].

The final results are presented in Fig.19, where retrofitting cost is presented for a single column considering all the 20 strategies used in this study. From Fig. A1 in Electronic Supplementary Material, it was estimated that there was a total of 29 columns on the ground floor, so to estimate the retrofitting cost for the whole story (since only ground floor columns are retrofitted in this study) the unit column cost for each strategy presented in Fig.19 was multiplied with the total No. of columns. The results are presented in Tab.6, in which total retrofitting costs for each strategy are estimated. It can be seen that SPJ-4 which performed relatively better among others in the vulnerability assessment, is costing almost 10 thousand dollars which is more than 4 times the cost of ECJ-1. The mean values of total retrofitting cost for SPJ, SAJ, RCJ, and ECJ are estimated as 8138.49, 6382.12, 4120.42, and 4314.46 USD, respectively. Hence the RCJ seems to be a more promising alternative as compared to the other ones. To make the comparison more effective, the normalized results are presented in Fig.20.

It can be seen that the minimum retrofit cost is offered by ECJ-1 and hence all the results are normalized by that value. The most expensive strategy is SPJ-5, followed by SPJ-4 and SPJ-3, respectively. The SPJ alternative, although showed superior performance in vulnerability assessment, however, their cost-effectiveness might hinder its acceptance as a feasible option. On the other hand, the rest of the retrofit strategies show decent results in terms of cost-effectiveness specially RCJ, since the main bars used were 8#5 and the stirrups used were #3@6 in, therefore the cost of RCJ was the least in the case of RCJ-3, RCJ-4, and RCJ-5 as compared to the other alternatives. Thus, making RCJ the more cost-effective alternative, followed by ECJ and SAJ, respectively.

A final comparison is made between the normalized VI (i.e., the least VI value among all the 20 models is taken as the datum, and VI of all models is divided by it) and normalized cost comparison for decision making, and results are presented in Fig.21. It can be seen that the SPJ alternative gives the least vulnerability but costs the most. On the other hand, the SAJ alternative possesses the greatest relative vulnerability, but the cost is comparatively less than that of SPJ-3 and onwards. The most promising results are obtained for RCJ and ECJ alternatives, where the VI doesn’t increase like SAJ, however the cost-effectiveness is most as compared to other alternatives. So RCJ stands first based on assumptions made in this study.

7 Global warming potential and CO₂ emission

Another important parameter for the selection of retrofit strategy considered in this study is the impact on the environment, e.g., the CO₂ emission during the construction and transportation of the retrofit material. While cost-benefit analysis focuses on the financial implications of retrofitting options, incorporating GWP in terms of CO₂ emissions can lead to long-term cost savings. Retrofitting solutions with lower environmental impacts may result in reduced operational costs, energy consumption, and maintenance requirements over the lifespan of the structure, translating into financial benefits in the long run. Carbon emissions calculation for steel is very subjective and varies greatly due to the production methods like Blast Furnaces and Basic Oxygen Furnace (BF-BOF) or Electric Arc Furnace (EAF) along with the content of recycled steel scrap. A list of the carbon emission factors of rebar and structural steel by Gan et al. [113] is presented in Appendix B in Electronic Supplementary Material, and the average value of EAF and BF-BOF are employed for structural steel and rebars. Thus, the CO₂-emission/kg values calculated are 1.18 and 1.15 kg for structural steel and steel rebar, respectively. To calculate the CO₂ emission of concrete along with all allied services, the green concrete LCA tool [114] is employed. This tool is normally designed to estimate the concrete’s environmental impact, considering the constituent materials (i.e., cement, aggregates, admixtures, and secondary cementitious materials (SCMs)), and the use of fuels and water. A summary of the assumptions used for the different production technologies, the percentages of power sources in the electricity grid mix of Pakistan, geographic locations, distances, modes of transport, and material types is given in Table B1 through Table B4 of Appendix B in Electronic Supplementary Material and are obtained from Azam et al. [115]. In the case of ECC, the CO₂ emission based on mix design and proportion of constituent materials is estimated from the study done by Bheel et al. [116].

Fig.22 presents the results of a detailed analysis of various retrofit alternatives in the form of CO₂ emission. In the case of the SAJ alternative, the CO₂ emissions are higher compared to other alternatives due to the energy-intensive manufacturing process of steel and the amount of steel used in it. Additionally, steel production is known to emit significant amounts of greenhouse gases, further contributing to its environmental impact. The range of SAJ alternatives is from 15860 to 19610 kg-CO₂, for SAJ-1 to SAJ-5 options, thus making it the least environment-friendly solution among the considered alternatives. The GWP of SPJ is also relatively high, as steel is a material with a high carbon footprint. However, retrofitting SPJ has slightly lower CO₂ emissions compared to SAJ, mainly due to the small thickness of the plates used, and therefore reduces the total quantity of steel used. However, the GWP of SPJ remains high due to the inherent environmental impact of steel production. The range of the SPJ alternative is from 5869 to 1367 kg-CO₂, for SPJ-1 to SPJ-5 options, thus making it the second-least environment-friendly solution, after the SAJ alternative. In the case of RC jacketing, the CO₂ emissions are considerably lower compared to SAJ and SPJ alternatives, but it is producing more CO₂ compared to ECJ alternatives. The range of the RCJ alternative is from 3677 to 5443 kg-CO₂, for RCJ-1 to RCJ-5 options, since, steel rebars are used in the RCJ alternative, thus the impact of this option is, therefore, more as compared to ECJ, but since the amount of steel used was very low, thus the impact was minimal as compared to SPJ and SAJ alternatives. Lastly, the ECJ alternative offers the lowest GWP in terms of CO₂ emissions among the alternatives, as ECC materials are designed to be more durable and sustainable than traditional concrete materials. ECC jacketing can significantly reduce the environmental impact of retrofitting while providing comparable structural performance. The range of ECJ alternatives is from 2087 to 4870 kg-CO₂, for ECJ-1 to ECJ-5 options, thus making it the most environment-friendly solution.

Overall, considering the GWP in terms of CO₂ emissions of retrofitting alternatives is crucial in making informed decisions that prioritize sustainability and environmental responsibility in structural retrofitting projects.

Fig.23 presents the final comparison of all the considered retrofit solutions in terms of normalized VI, retrofit cost, and CO₂ emission, to select the most feasible option. All the values are normalized in a relative manner, where the VI values are normalized against the smallest VI value among the retrofit solutions and therefore the lowest value obtained on the vertical axis is one. The same procedure is adopted for retrofit cost and CO₂ emission results and the normalized values with a minimum value of 1 are plotted for the sake of comparison and ease in the decision-making process. Fig.23 clearly shows that the VI value for all the retrofitting options are almost in the same range (i.e., between 1 and 1.4) and the decision should be governed by the other two parameters i.e., cost and GWP which indicates that the ECJ alternative is offering the most cost-effective solution in terms of retrofit cost as well as CO₂ emission minimization. For instance, ECJ-1 gives the normalized value of 1 for both the retrofit cost and GWP, thus making it to be the most suitable retrofit solution. Similarly, ECJ-2 gives the least values close to the ECJ-1, followed by RCJ-1. Thus, ECJ stands out as the most promising solution closely followed by RCJ solution. However, the steel options (SPJ and SAJ) are not as cost-effective in terms of retrofit cost as well as carbon emission and therefore the least suitable options in the considered circumstances.

8 Conclusions

This study proposes a performance-based method for estimating the seismic vulnerability, under traditional structural retrofit practices. A hospital building is taken as a reference in the case study since hospitals are among the critical structures that need to be functional all the time and most importantly after a natural hazard, to provide medical service wherever needed. Nonlinear pushover analysis is selected as the approach to determine the structural response since it is the most cost-effective computation approach that can be performed with greater accuracy and simplicity. The capacity curves are generated and used to determine the vulnerability and behavior is estimated and compared for the said reference structure before and after the retrofitting, considering four different techniques. It should be noted that retrofitting was applied to the columns of the ground floor only. It is determined from the results that retrofitting lessens the probability of collapse, i.e., seismic vulnerability and risks are reduced.

Based on the study performed, the following conclusions are made.

1) The proposed framework effectively assesses the seismic vulnerability of structures and suggests retrofitting solutions. In total, four retrofit options were considered to improve the performance of the structure: RCJ, SPJ, SAJ, and ECJ. Among these alternatives, the SPJ option proves to be the most effective in reducing vulnerability and enhancing the lateral load-resisting capacity of the structure. Following SPJ, the SAJ option is also effective, while RCJ and ECJ exhibit comparatively lesser effectiveness, with the former being more effective than the latter.

2) This study focuses on a relatively new retrofit strategy known as ECC jacketing, which is evaluated alongside three other alternatives. ECJ is the most effective retrofitting technique for structural performance, cost, and environmental impact compared to alternatives like SPJ, SAJ, and RCJ.

3) The mean vulnerability indices (VIs) for the SPJ, SAJ, RCJ, and ECJ alternatives are calculated to be 0.69, 0.79, 0.73, and 0.74, respectively. These values suggest that the SPJ alternative is particularly effective in reducing the seismic vulnerability of the structure, especially when compared to the reference structures, which have a VI of 0.89. Additionally, the collapse fragilities obtained further support these findings, highlighting both the reliability of the VI method and the efficacy of retrofitting alternatives in mitigating seismic vulnerability.

4) When comparing CO₂ emissions alongside retrofit costs and vulnerability indices, the ECJ alternative emerges as the most viable solution, demonstrating both the lowest retrofit costs and CO₂ emissions, closely followed by the RCJ alternative. In contrast, the SPJ and SAJ alternatives rank as the least favorable options, particularly when CO₂ emissions are taken into account, despite their advantages in reducing seismic vulnerability. Therefore, the ECJ method not only yields lower CO₂ emissions than traditional retrofitting techniques but also represents a more sustainable choice for enhancing sustainability. It is essential to adopt a multi-faceted approach in identifying the key parameters that stakeholders should consider.

Further research is needed to explore the full potential and long-term benefits of ECC jacketing for retrofitting purposes, particularly in comparison with the traditional materials to better estimate the superior quality and performance offered by it.

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