Interview Questions for Seismic Vulnerability Assessment

Seismic hazard and seismic risk are closely related but distinct concepts. Seismic hazard refers to the probability of a seismic event (earthquake) of a certain magnitude occurring at a specific location within a given timeframe. It’s essentially the potential for an earthquake to happen. Think of it like the potential for a hurricane in a coastal region – we know hurricanes can happen there, and we can assess the likelihood based on historical data and geological factors. On the other hand, seismic risk is the potential for loss (economic, social, or environmental) due to the earthquake. It incorporates the hazard along with the vulnerability of the structures and the population within the hazard zone. Risk is a consequence of hazard.

For example, a region might have a high seismic hazard (frequent and powerful earthquakes), but if the buildings are all earthquake-resistant, the seismic risk might be low. Conversely, a region with a moderate seismic hazard but poorly constructed buildings will have a high seismic risk. Seismic risk assessment involves quantifying this risk, combining hazard and vulnerability information.

Assessing the seismic vulnerability of structures involves a multi-faceted approach that utilizes various methods depending on the complexity of the structure and the level of detail required. These methods include:

• Visual inspection: This is a basic yet crucial method, involving a detailed visual examination of the structure to identify visible signs of damage, deterioration, or poor construction practices that could compromise its seismic performance. This can reveal things like cracked walls, damaged columns, or weak connections.
• Linear elastic analysis: This method uses simplified computer models to predict structural response to earthquake forces. While faster and easier to implement than nonlinear analysis, it’s only useful for preliminary evaluations as it doesn’t capture the effects of material nonlinearity, which is crucial in strong earthquakes.
• Nonlinear dynamic analysis: This advanced technique uses complex computer models that account for the material nonlinearity and the dynamic nature of seismic loads. It provides more accurate estimations of the structural response during an earthquake, especially for large earthquakes exceeding the structure’s elastic capacity.
• Pushover analysis: This method simulates the gradual application of increasing lateral forces to a structure until collapse. It helps determine the structure’s capacity and the associated deformation levels, allowing for the identification of weak points.
• Fragility analysis: This probabilistic approach combines structural models with seismic hazard information to estimate the probability of exceeding specific damage states at different earthquake intensities. This is essential for risk assessment, as discussed later.

The choice of methods will usually depend on the available resources, the urgency of the assessment, and the level of accuracy required. For critical infrastructure, nonlinear methods are preferred, while preliminary assessments or smaller structures might only justify linear analysis or visual inspections.

Linear elastic analysis, while useful for preliminary assessments and simpler structures, has significant limitations in seismic vulnerability assessment. Its primary limitation is the assumption of linear material behavior. Real-world materials, such as concrete and steel, exhibit nonlinear behavior, meaning their stiffness changes significantly under large loads. In an earthquake, structures often experience forces beyond their elastic limit, causing significant inelastic deformation.

Linear elastic analysis fails to capture this inelastic behavior, leading to underestimation of damage and potential collapse. It doesn’t account for effects like yielding of steel, cracking of concrete, or the degradation of stiffness during an earthquake. These factors significantly affect the structure’s strength and ductility, therefore it should only be used as a first step for simple preliminary studies.

For accurate assessment of seismic vulnerability, particularly for structures in high seismic zones, nonlinear dynamic analysis is necessary to capture this crucial inelastic behavior and provide a more reliable prediction of the structural response to seismic loads.

Soil conditions play a critical role in seismic vulnerability assessments because they significantly influence the intensity and characteristics of ground shaking during an earthquake. Different soil types exhibit varying degrees of stiffness, damping, and amplification characteristics. These characteristics influence the ground motion experienced at the foundation of a structure.

Incorporating soil conditions involves the following:

• Site investigation: This involves conducting geotechnical investigations to determine the soil profile, including soil type, density, shear strength, and liquefaction potential.
• Soil response analysis: This involves using numerical models or empirical methods to simulate the behavior of the soil during an earthquake and determine the amplification of ground motion at the site. This accounts for things like soil layering, stiffness variations, and potential liquefaction.
• Ground motion modification: The results of the soil response analysis are used to modify the input ground motion used in the structural analysis, ensuring that the structure is subjected to realistic seismic excitations that reflect the local soil conditions.

For instance, soft, saturated soils can significantly amplify ground motion, leading to increased seismic demands on structures compared to those founded on stiff rock. Ignoring soil conditions can lead to grossly inaccurate and unsafe vulnerability assessments, significantly impacting design decisions and mitigation strategies.

Fragility curves are probabilistic models that describe the relationship between the intensity of ground shaking (usually expressed as Peak Ground Acceleration or PGA) and the probability of a structure exceeding a specific damage state. They are fundamental tools in seismic risk assessment, providing a quantitative measure of a structure’s vulnerability.

A fragility curve is typically represented graphically, with the horizontal axis representing the intensity of ground shaking (e.g., PGA) and the vertical axis representing the probability of exceeding a specific damage state (e.g., slight, moderate, extensive, or collapse). The curve shows a sigmoidal shape; the probability increases gradually as the ground shaking intensity increases. For example, a fragility curve for a ‘collapse’ damage state would show a near-zero probability of collapse at low PGA values, gradually increasing to higher probabilities as PGA increases beyond a certain threshold.

Applications: Fragility curves are crucial in seismic risk assessment because they allow us to estimate the probability of different damage levels given a specific seismic hazard scenario. This information is then used to estimate potential economic losses, casualties, and disruptions to essential services, thus informing decision-making for mitigation and preparedness.

Seismic retrofitting involves modifying existing structures to improve their resistance to earthquake damage. The choice of technique depends on the structure’s type, age, and existing deficiencies. Here are some common techniques:

• Base isolation: This technique decouples the structure from the ground motion using bearings, reducing the forces transmitted to the superstructure.
• Structural strengthening: This involves increasing the structural capacity by adding strengthening elements like steel bracing, shear walls, or jacketing of columns.
• Improved connections: Strengthening or replacing weak connections between structural elements, such as beam-column joints.
• Soil improvement: Techniques like densification or grouting to improve the soil’s bearing capacity and reduce the risk of liquefaction.
• Infill wall strengthening: Strengthening or replacing infill masonry walls, which can be a source of weakness in many older buildings.

The effectiveness of each technique depends on various factors, including the specific structure, the type of ground shaking, and the quality of construction. A thorough engineering assessment is essential to select the most appropriate and effective retrofitting strategies, ensuring the enhanced seismic performance and safety of the structure.

Determining the appropriate level of seismic design for a structure is a complex process that considers several factors, including:

• Seismic hazard: The probability and intensity of earthquakes at the site. This is determined from seismic hazard maps and ground motion prediction equations.
• Occupancy and importance: Essential facilities, such as hospitals and fire stations, require a higher level of seismic design than non-essential buildings.
• Building code requirements: Building codes specify minimum seismic design requirements based on the seismic hazard and occupancy category.
• Economic considerations: The cost of implementation versus the potential losses due to earthquake damage. This involves a risk-based approach, balancing the cost of mitigation with the potential losses.
• Life-cycle cost analysis: Evaluating the total cost of the structure over its lifespan, including construction, maintenance, and potential repair costs after an earthquake.

The design process usually involves a performance-based approach, aiming to achieve specific performance goals, such as limiting damage levels to a certain level or ensuring structural safety under extreme seismic events. This often involves iterative analysis and design, refining the design until the desired performance targets are met. The decision ultimately rests on the balance of these competing factors, aiming for an optimal design that provides adequate seismic protection at an acceptable cost.

The seismic performance of a building hinges on a complex interplay of factors. Think of it like building a house of cards – even a small tremor can bring it down if the foundation isn’t strong. Similarly, various elements contribute to a building’s ability to withstand an earthquake.

• Site Conditions: The soil type significantly impacts ground shaking. Soft soils amplify ground motion, while bedrock offers more stability. Imagine building on a sand dune versus a solid rock foundation – the former is far riskier.
• Structural System: The type of structural system (e.g., moment-resisting frames, shear walls, braced frames) dramatically affects its ability to absorb seismic energy. A well-designed structure can flex and dissipate energy, reducing damage.
• Building Materials: The strength and ductility of materials are crucial. Ductile materials, like steel, can deform significantly under stress without fracturing, offering more resilience than brittle materials, like unreinforced masonry.
• Construction Quality: Proper construction techniques are paramount. Poor workmanship can lead to premature failure, even in well-designed structures. It’s like baking a cake – the ingredients might be perfect, but if you don’t follow the recipe correctly, the outcome suffers.
• Building Geometry and Irregularities: Irregular shapes or changes in stiffness can concentrate seismic forces in specific areas, creating weak points. Imagine a building with a sudden change in height – that area is more likely to experience increased stress during an earthquake.
• Foundation Design: A well-designed foundation ensures proper load transfer from the structure to the soil. Inadequate foundations can lead to structural instability.

Understanding and optimizing these factors is vital for designing seismically resilient structures.

Non-structural components, while not directly supporting the building’s weight, significantly impact its functionality and safety during and after an earthquake. Think of all the things inside a building – ceilings, partitions, mechanical equipment, etc. These components can become dangerous projectiles during a quake, causing injuries or further damage.

Considering non-structural components in seismic design is crucial for several reasons:

• Life Safety: Falling ceilings or equipment can cause serious injury or death. Proper bracing and anchoring of these elements is vital for occupant protection.
• Functionality: Damage to non-structural elements can render a building unusable even if the structural frame remains intact. Imagine a hospital where medical equipment is damaged – this can be catastrophic.
• Economic Losses: Repairing damaged non-structural components can be expensive, adding to the overall cost of earthquake recovery.

Effective strategies include using flexible connections, appropriate bracing, and impact-resistant materials. For instance, properly anchored suspended ceilings can significantly reduce the risk of collapse.

Uncertainty is inherent in seismic hazard and vulnerability assessments. We’re essentially trying to predict the unpredictable – the occurrence of a rare and complex event. To account for this, we employ probabilistic methods.

Probabilistic Seismic Hazard Analysis (PSHA) is a common approach. Instead of predicting a single earthquake, PSHA calculates the probability of exceeding various ground motion levels over a specified period. This provides a range of potential ground motions rather than a single, potentially inaccurate value.

Vulnerability assessments also incorporate uncertainties through fragility curves. These curves depict the probability of exceeding a specific damage state (e.g., slight damage, collapse) given a certain ground motion intensity. This allows us to capture the inherent variability in building response.

Furthermore, we utilize Monte Carlo simulations to propagate uncertainties through the analysis. This involves running numerous simulations with different input parameters (drawn from probability distributions) to obtain a range of possible outcomes and better understand the overall uncertainty.

By acknowledging and quantifying these uncertainties, we can design structures that are appropriately robust and resilient, ensuring a suitable margin of safety.

Building codes play a critical role in seismic safety by establishing minimum requirements for structural design and construction. They are essentially the rulebook for ensuring that buildings are designed and built to withstand anticipated seismic forces. They are based on the best available scientific knowledge and engineering practice.

Building codes don’t guarantee buildings will survive every earthquake, but they significantly improve the odds of minimizing damage and protecting life. They define:

• Design forces: The level of seismic forces a building must withstand.
• Material properties: Acceptable materials and their required properties.
• Construction techniques: Acceptable construction methods and quality control measures.
• Inspection and enforcement: Procedures to ensure compliance with the code.

Regular updates to building codes reflect advancements in seismic engineering research and our understanding of earthquake hazards. They are a crucial tool for reducing seismic risk and improving community resilience.

I have extensive experience in seismic microzonation, a process that involves dividing an area into zones based on their seismic response characteristics. This is like creating a detailed map highlighting areas that are more or less susceptible to earthquake damage. Think of it as tailoring seismic design to specific locations within a larger region.

My work has included conducting geophysical investigations, analyzing soil properties, and developing ground motion prediction equations tailored to the specific characteristics of each microzone. I’ve used this information to refine seismic design parameters for buildings and infrastructure within these microzones, leading to more accurate and effective seismic hazard assessments. For example, in one project, we identified a zone with amplified ground motion due to soft soil, leading to a significant increase in design seismic forces for structures built in that area.

I’m proficient in several software and tools for seismic analysis, including:

• SAP2000: A widely used finite element analysis software for structural analysis and design.
• ETABS: Another popular software for performing structural analysis of buildings, particularly those with complex geometries.
• OpenSees: An open-source platform for performing nonlinear structural analysis, allowing for detailed modeling of complex material behaviors.
• R/Python: I utilize R and Python for statistical analysis, probabilistic seismic hazard analysis (PSHA), and data processing.

My proficiency extends to using these tools not only for individual analyses but also for integrating different aspects of seismic vulnerability assessments, from hazard analysis to damage estimation.

Interpreting seismic records and assessing their impact on structures involves a multi-step process. It’s like a detective piecing together clues to understand what happened.

First, I would review the characteristics of the recorded ground motion, including peak ground acceleration (PGA), peak ground velocity (PGV), and spectral accelerations at various periods. These parameters provide insights into the intensity and frequency content of the earthquake shaking.

Next, I’d correlate these ground motion parameters with the dynamic properties of the structure. This involves analyzing the building’s natural frequencies and mode shapes. The degree of overlap between the earthquake’s frequency content and the structure’s natural frequencies determines the level of response. If the frequencies match, the response is amplified, leading to potentially greater damage.

Finally, using engineering models (often nonlinear), I’d simulate the structure’s response to the recorded ground motion. This allows me to estimate the potential damage levels, identify vulnerable elements, and inform repair strategies. This process could be supported by visual inspection of the structure if possible to corroborate the simulation results.

The Capacity Spectrum Method (CSM) is a powerful tool in seismic engineering used to assess the seismic performance of structures. It compares the structure’s capacity (its ability to resist earthquake forces) to the demands imposed by the earthquake. Instead of performing complex nonlinear dynamic analyses for every earthquake scenario, CSM simplifies the process by representing both capacity and demand graphically.

Imagine a graph with the spectral acceleration (a measure of earthquake intensity at different periods) on the y-axis and the displacement on the x-axis. The structure’s capacity is represented by a curve showing its strength and ductility. The earthquake’s demand is also represented as a curve, showing the forces it imposes at different displacement levels. The intersection of these two curves indicates the expected performance level of the structure under that specific earthquake.

For example, if the demand curve lies entirely below the capacity curve, the structure is expected to perform well, with minimal damage. However, if the demand curve significantly exceeds the capacity curve, the structure might experience significant damage or even collapse. CSM allows engineers to quickly assess the potential damage levels and guide design or retrofitting decisions.

In practice, CSM uses simplified models and readily available spectral data to create these curves, significantly reducing the computational burden compared to other methods. This makes it suitable for a wide range of applications, from preliminary design checks to detailed assessments of existing buildings.

My experience with performance-based seismic design (PBSD) spans several projects, including the design of a new hospital in a high-seismic zone. Instead of just meeting minimum code requirements, PBSD focuses on defining specific performance objectives, such as limiting damage to a certain level or ensuring functionality after an earthquake of a given intensity. This approach necessitates a thorough understanding of the structure’s behavior under seismic loading and the use of advanced analytical techniques.

In the hospital project, we utilized nonlinear time-history analysis to model the structure’s response to several earthquake scenarios. This allowed us to assess various design parameters and identify the optimal design to achieve our performance objectives – minimal structural damage and continued functionality after a major earthquake. We also considered the importance of non-structural components (like medical equipment and life safety systems), ensuring their protection through appropriate design considerations.

Furthermore, my work involved the probabilistic seismic hazard analysis (PSHA) which informed the selection of the design earthquake. PSHA uses statistical approaches to consider the potential occurrence of multiple earthquakes and quantify associated uncertainties.

PBSD allows for optimization of designs, leading to cost-effective yet robust structures that meet specific performance targets, aligning with client needs and risk tolerance.

Assessing liquefaction potential involves several steps, beginning with a thorough site investigation. This includes collecting soil samples for laboratory testing to determine the soil’s grain size distribution, density, and plasticity characteristics. These data are crucial for determining the soil’s susceptibility to liquefaction.

Next, we use empirical methods, such as the simplified procedures outlined in various geotechnical engineering guidelines (e.g., those provided by the USGS). These methods utilize readily available data like the soil’s parameters (obtained from laboratory tests or in-situ measurements) and the expected ground motion characteristics during an earthquake to determine the factor of safety against liquefaction. A factor of safety less than 1 indicates a high likelihood of liquefaction.

Advanced techniques, such as cyclic triaxial testing or dynamic centrifuge modelling, can provide more refined estimations of liquefaction potential, particularly for complex soil profiles or critical infrastructure. These methods directly simulate the effects of earthquake shaking on soil samples.

For example, on a recent project involving a large dam, we conducted both in-situ and laboratory tests. The results were inputted into a probabilistic liquefaction analysis, which considered the uncertainties associated with the soil properties and seismic loading. This comprehensive approach ensured a robust evaluation of liquefaction risks, allowing for appropriate mitigation measures such as ground improvement techniques (e.g., soil densification or vibro-compaction).

My experience with seismic instrumentation and monitoring encompasses various aspects, from designing and deploying sensor networks to analyzing the collected data to understand structural behavior during earthquakes. I’ve been involved in projects installing accelerometers, strong-motion sensors, and displacement transducers in structures ranging from buildings and bridges to dams.

In one project, we instrumented a high-rise building with a network of accelerometers and displacement sensors to monitor its response during induced vibrations and aftershocks of a major earthquake. The data collected provided valuable insights into the actual structural behavior under seismic loading, which we used to validate our analytical models and refine our understanding of the structure’s resilience. This helped to identify any unexpected modes of failure and potentially inform any necessary upgrades.

The data analysis often involves sophisticated signal processing techniques to isolate and interpret meaningful information from the raw sensor data. We also apply advanced algorithms and machine learning techniques to detect anomalies or predict potential future behavior, further improving the effectiveness of structural health monitoring.

Seismic damage to buildings arises from a variety of factors. One of the most common causes is insufficient strength or ductility to withstand the inertial forces generated during shaking. This can lead to various forms of damage, including cracking, crushing, or collapse.

• Lack of adequate detailing: Poor detailing, such as inadequate connection design between structural elements, often results in premature failure. Improper lap splices in reinforced concrete columns are a common example.
• Soft Story Collapse: Buildings with weaker ground floors (often due to parking garages or open spaces) are prone to collapse. The lateral stiffness difference between stories significantly amplifies the response of weaker stories.
• Foundation failure: Inadequate foundation design or soil liquefaction can lead to foundation settlement or instability, ultimately compromising the structural integrity of the entire building.
• Torsional effects: Eccentricity of mass or stiffness can induce significant torsional moments, which can exacerbate damage, particularly in irregular buildings.
• Resonance: If the building’s natural frequency matches the predominant frequency of ground motion, resonance can amplify the response significantly leading to severe damage.

Understanding these mechanisms is crucial for designing earthquake-resistant structures and mitigating damage in existing buildings.

Prioritizing retrofitting of existing buildings requires a multi-faceted approach that integrates seismic risk assessment, cost-benefit analysis, and societal considerations. A common method is to use a seismic risk matrix that considers the building’s vulnerability (likelihood of experiencing damage) and the potential consequences of failure (e.g., loss of life, economic losses).

We typically start by conducting a thorough seismic vulnerability assessment of each building, including structural inspections and analyses. This assessment determines the building’s capacity to withstand future earthquakes, which can then be compared against predicted ground motions. This information helps to quantify the building’s risk profile.

Next, we evaluate potential retrofitting strategies, carefully considering their effectiveness and costs. A cost-benefit analysis comparing the cost of retrofitting with the potential reduction in future losses is critical. Finally, we consider the occupancy type and societal importance of the building. Hospitals and schools, for instance, would receive higher priority due to their critical functions and potential for significant human losses in case of an earthquake.

This process allows us to develop a prioritized list of buildings for retrofitting, focusing resources on the structures that pose the greatest risk to life safety and have the highest potential for economic loss reduction.

My experience with seismic loss estimation encompasses both empirical and analytical methods. Empirical methods rely on statistical relationships between earthquake intensity, building characteristics, and observed damage patterns from past events. These methods are relatively straightforward but may not accurately capture the complexities of specific building designs or site conditions.

Analytical methods, on the other hand, involve simulating the structural response of buildings to earthquake ground motions using advanced computer models. These methods offer higher accuracy but require detailed knowledge of building characteristics and can be computationally intensive. The choice of method depends on the project’s scope, the available data, and the level of accuracy needed.

For example, on a recent project involving a portfolio of commercial buildings, we utilized a hybrid approach. We used empirical models to obtain preliminary loss estimates for simpler buildings, while using more sophisticated nonlinear analysis for buildings with complex designs or those located in areas with high seismic hazard. This allowed for a cost-effective approach while ensuring the required level of accuracy for the critical structures. The final output includes both direct losses (e.g., repair costs) and indirect losses (e.g., business interruption costs). Loss estimation is a critical element in seismic risk management, guiding decision-making on investments in earthquake mitigation.

Seismic resilience refers to the ability of a community, system, or structure to withstand, absorb, accommodate, recover from, or adapt to the effects of a seismic event. It’s not just about preventing damage, but about minimizing disruption and ensuring rapid recovery. Think of it like a flexible tree bending in the wind – it survives the storm because it can adapt. A brittle structure, on the other hand, like a rigid building, might crumble.

The importance of seismic resilience is paramount, especially in seismically active regions. It translates to saving lives, reducing economic losses, and protecting essential infrastructure. A resilient community can bounce back quicker from an earthquake, minimizing the long-term social and economic consequences.

• Reduced Loss of Life: Resilient designs prioritize life safety through features like strong foundations and ductile structural elements that can absorb energy.
• Minimized Economic Disruption: Quick recovery means businesses can resume operations sooner, minimizing economic losses and job displacement.
• Enhanced Community Preparedness: A resilient community invests in preparedness measures like early warning systems and emergency response plans.

Communicating technical information effectively to non-technical audiences requires simplification and visualization. I avoid jargon and use plain language, employing analogies and real-world examples to illustrate complex concepts. For instance, when explaining seismic waves, I might compare them to ripples in a pond after throwing a stone. Visual aids such as charts, diagrams, and even short videos are crucial. I also focus on the implications of the information, explaining how it affects their lives or the community. For instance, rather than focusing on shear strength calculations, I’d highlight how a specific design choice enhances the building’s safety during an earthquake.

Active listening is equally important. I ensure I understand their level of understanding and tailor my communication accordingly, answering questions patiently and clearly.

My experience with multidisciplinary teams is extensive. Seismic vulnerability assessments are inherently collaborative endeavors, involving geologists, geotechnical engineers, structural engineers, architects, urban planners, and social scientists. In one project, assessing the seismic resilience of a historical city center, I collaborated with historians to understand the building materials and construction techniques used centuries ago. The geologists provided crucial information on the local soil conditions and potential ground shaking amplification. This collaboration ensured a holistic assessment, considering not only the structural aspects but also the social and economic implications of potential damage.

Effective communication and mutual respect are vital for successful collaboration. I employ regular meetings, shared online platforms for data exchange, and clear documentation protocols to ensure seamless teamwork and prevent misunderstandings.

I’ve been involved in several projects related to seismic code development and implementation. This has included reviewing and updating existing codes based on the latest research and advancements in seismic engineering. One significant project involved contributing to the revision of a national building code, incorporating updated provisions for seismic design and detailing of structures. This required deep understanding of engineering principles, statistical analysis of earthquake data, and collaborative efforts with policymakers and stakeholders. The goal was to balance safety requirements with practical considerations for the construction industry, ensuring the code is both effective and implementable.

Another aspect of my work has been assisting communities in implementing the code effectively through workshops and training programs for engineers and builders.

Several emerging trends are shaping the field of seismic vulnerability assessment. The increasing use of advanced computational techniques, such as high-performance computing and machine learning, allows for more sophisticated simulations of earthquake behavior and structural response. This leads to more accurate assessments of vulnerability and better-informed mitigation strategies.

Another trend is the integration of geospatial data and remote sensing technologies. This enables detailed mapping of vulnerable areas and infrastructure, facilitating targeted interventions and resource allocation. Furthermore, the focus on community resilience emphasizes not just the physical structures but also the social and economic aspects of recovery, leading to more holistic and sustainable solutions.

Finally, performance-based seismic design is gaining traction, moving beyond prescriptive code compliance to focus on achieving specific performance objectives under earthquake loading conditions.

Staying updated in seismic engineering requires a multi-pronged approach. I actively participate in professional organizations like the Earthquake Engineering Research Institute (EERI) and attend international conferences and workshops to learn about the latest research findings and best practices. I subscribe to leading journals in the field and regularly review relevant publications. Online resources, including databases of earthquake records and engineering software updates, are also invaluable. Moreover, continuous professional development through specialized courses and training programs ensures my skills and knowledge remain current.

One particularly challenging project involved assessing the seismic vulnerability of an old, densely populated city with a complex network of interconnected structures and narrow streets. The challenge was to balance the need for detailed analysis with the logistical constraints of conducting field surveys in a crowded environment. The historical significance of many structures added another layer of complexity, requiring careful consideration of preservation requirements while ensuring public safety.

To overcome this, we employed a phased approach. We began with a preliminary assessment using readily available data, including historical records and satellite imagery. This allowed us to identify the most vulnerable areas and prioritize field surveys. We then used non-destructive testing methods to minimize disruption in the densely populated areas. Furthermore, we developed a collaborative framework with the local community to ensure smooth data collection and acceptance of our recommendations. This involved community workshops to explain our findings and their implications, ensuring the final report was both technically sound and socially acceptable.