The research, led by Dongyeon Lee of Hanyang University together with colleagues from Korea Hydro and Nuclear Power and the Korea Advanced Institute of Science and Technology, tackles a long-standing gap in earthquake engineering practice. Spatial coherency describes how the similarity between ground motions at two locations decays as the separation between them grows and as the frequency of the shaking increases. Empirical models built from dense arrays such as those at Lotung in Taiwan or Chiba in Japan have long served as the reference standard, but they are inherently site-specific. Extending them to a new site means installing instruments and waiting for earthquakes to happen, which is neither practical nor economical for most engineering projects. The Korean team’s alternative is to predict coherency from first principles, using the measured spatial statistics of the soil itself as the input.

The physical basis of the new framework is the recognition that incoherency at a single site arises largely from the heterogeneity of the subsurface. Shear waves traveling upward through soil encounter pockets and layers of varying stiffness, and each encounter scatters and delays the wavefield slightly differently at every location. If the spatial distribution of shear wave velocity, denoted Vs, is known in statistical terms, the resulting distortion of the wavefield can, in principle, be computed. The researchers therefore set out to measure Vs variability directly and feed those statistics into a two-dimensional finite-element model of the soil deposit, generating Gaussian random fields whose coefficient of variation and correlation lengths match the field measurements.

Validating such a framework requires ground truth, and this is where the centrifuge enters the story. Geotechnical centrifuges allow engineers to test scaled physical models of soil deposits under properly scaled gravitational stress, reproducing the stress-dependent stiffness and damping behavior that governs wave propagation at full scale. The team constructed two soil models in the centrifuge, one a single-layered deposit and the other a double-layered deposit, and subjected them to recorded earthquake motions using an on-board earthquake simulator. Crucially, they characterized the spatial variability of the models themselves using bender elements and cone-penetration tests at multiple locations, obtaining the coefficient of variation and correlation lengths needed to build representative random fields. This pairing of physical testing and statistical characterization is what gives the study its unusual rigor.

On the computational side, each physical model was represented by a two-dimensional finite-element mesh, and the researchers ran a substantial campaign of simulations: ten bedrock motions recorded during the centrifuge tests were combined with thirty random-field realizations for each model, producing three hundred time-history analyses per deposit. Each realization represents one plausible arrangement of the measured soil heterogeneity, and the ensemble captures the range of responses that variability can produce. From the simulated surface motions at multiple locations, the team computed coherency functions in the same manner used for array recordings, binning results by separation distance so that they could be compared directly with the coherency derived from the centrifuge sensors.

The agreement reported is striking. The numerical models closely reproduced the measured response spectra and the shear stress-strain behavior observed in the centrifuge, confirming that the wave propagation physics was being captured correctly. More importantly for the study’s central claim, the coherency models computed from the simulations showed strong agreement with the centrifuge-derived coherency across all separation-distance bins. In other words, once the spatial variability statistics of the soil are known, the simulation does not merely approximate the general character of incoherency; it tracks the measured decay of coherency with distance and frequency in detail.

The implications extend well beyond the laboratory. Sites hosting critical infrastructure, particularly nuclear facilities, increasingly demand site-specific coherency models for soil-structure interaction analysis, and regulators in several countries have pressed for models tailored to local conditions. In Korea, for example, recent work has focused on generating coherency models suitable for nuclear power plant sites where no dense arrays exist. A validated simulation-based framework means that a project team could characterize a site with conventional geotechnical investigation tools, bender element tests and cone-penetration soundings are routine in practice, and then compute a coherency model numerically rather than waiting years for array data to accumulate. The study’s authors present this as a practical alternative to empirical models whenever site-specific spatial variability parameters are available.

The work also connects to a broader trend in geotechnical engineering: the treatment of soil spatial variability as a quantifiable random field rather than a nuisance to be averaged away. Probabilistic approaches using random-field theory have transformed reliability analysis of slopes, foundations, and liquefaction assessments over the past two decades. What this study adds is a bridge between that statistical tradition and the wave-propagation community concerned with spatially varying earthquake ground motion. By demonstrating that measured Vs statistics suffice to predict coherency, the researchers effectively show that the two communities’ toolkits can be combined, with site investigation data flowing directly into ground-motion incoherency predictions.

There are, of course, boundaries to what the framework has so far demonstrated. The validation was performed on idealized laboratory deposits in a centrifuge, where the soil variability could be measured exhaustively and the input motions were fully known. Real field sites present additional complications, including three-dimensional subsurface topography, deeper and more variable layering, and uncertainty in bedrock input motions. The authors note that their findings establish the feasibility of simulation-based coherency estimation, and extending the approach to field conditions is the natural next step. Even so, the core result stands: the physics linking soil heterogeneity to ground-motion incoherency is now demonstrably reproducible in a validated numerical setting.

For engineers designing the next generation of long-span bridges, lifeline networks, and nuclear structures, the message is that coherency analysis need no longer be the exclusive privilege of instrumented sites. A well-characterized soil profile, a finite-element model, and a modest computational campaign of random-field realizations can deliver a defensible, site-specific coherency model, one that has now been checked against physical reality at centrifuge scale. As seismic design codes continue to move toward performance-based criteria that explicitly account for the spatial character of shaking, tools of this kind are likely to move from research papers into standard practice, changing how the profession thinks about what lies beneath the foundations of everything it builds.

Subject of Research: Centrifuge-validated numerical simulation of spatial seismic ground-motion coherency in heterogeneous soil deposits

Article Title: Centrifuge-validated numerical framework for estimating seismic coherency

Article References: Lee, D., Lee, Y., Choi, D.-H., Kwon, T.-H., & Park, D. (2026). Centrifuge-validated numerical framework for estimating seismic coherency. Bulletin of Earthquake Engineering. https://doi.org/10.1007/s10518-026-02714-3

Image Credits: AI Generated

DOI: 10.1007/s10518-026-02714-3

Keywords: seismic coherency, spatial variability, shear wave velocity, centrifuge testing, finite element analysis, Gaussian random fields, site response, soil-structure interaction, earthquake engineering, geotechnical engineering, dense seismic arrays, Bulletin of Earthquake Engineering

Researchers Kasif Furkan Ozturk, Tufan Cakir and Onur Araz of Gümüşhane University examined how the frequency content of ground motions and the thickness of such an isolation layer jointly govern the dynamic response of a five-story building. Their parametric study, published in the Bulletin of Earthquake Engineering, combined analytical modeling with a carefully classified set of earthquake records, comparing the structure resting on natural soil against the same structure founded on a geotechnical seismic isolation, or GSI, layer of six different thicknesses. The results carry practical weight for designers considering this technology.

The appeal of GSI systems lies in their simplicity of concept. Rather than installing mechanical base isolators, such as lead rubber bearings or friction pendulum devices, between a structure and its foundation, engineers instead surround or underlie the foundation with a engineered soil mixture, often soil blended with granulated scrap tire rubber. This softer, more damping-rich medium partially absorbs and dissipates seismic energy before it can climb into the building, filtering the shaking at the ground level itself. Because the approach recycles petroleum-derived waste materials such as discarded tires, it also addresses a genuine gap in waste recovery, turning an environmental liability into structural protection.

To test how well this filtering survives the messy variety of real earthquakes, the researchers grouped their ground motions according to frequency content and ran dynamic analyses across the full set. The findings on this front were consistent and, in some respects, sobering. For structures founded both on natural soil and on GSI layers, earthquakes with low frequency content produced structural responses greater than the average responses calculated across all the investigated records. In other words, slow, long-period ground motions tended to be the harshest critics of the building, regardless of what was buried beneath its foundations, and designers who evaluate structures against a generic suite of motions without regard to frequency content risk underestimating the demands that the most damaging classes of events can impose.

This frequency dependence echoes a growing body of research on soil-structure interaction. Previous work by members of the same group has shown that the frequency character of ground motion shapes the seismic response of retaining walls, box culverts, and buildings of varying aspect ratio when interaction with the surrounding soil is included. The new study extends that lesson into the GSI domain, confirming that an isolation layer does not erase the influence of how the shaking oscillates through time; the layer reshapes and attenuates the transmitted motion, but the character of the input still leaves its fingerprint on the building above.

The thickness of the isolation layer emerged as the other central variable, and here the study delivers its most actionable result. Increasing GSI thickness significantly attenuates structural responses, as expected, since a thicker compliant layer forces more of the seismic energy to deform and dissipate within the mixture rather than propagate upward. But the relationship is not linear, and the benefits diminish decisively with depth. Beyond a thickness of three meters, the researchers found that adding more material does not lead to a relatively significant further reduction in the dynamic responses of the investigated structural system.

That finding translates directly into a design recommendation. For the structural system, the natural soil conditions, the rubber-soil mixtures, and the earthquakes examined in the study, the authors suggest that selecting a GSI thickness in the range of two to three meters, inclusive, may be regarded as a practical approach for mitigating dynamic responses. Thicknesses beyond that range provide only progressively limited improvements, meaning the extra excavation, material, and cost buy shrinking returns. The proposal offers engineers a defensible starting point for a technology that has historically lacked the codified design procedures available for conventional base isolation.

The broader context makes the study timely. Geotechnical seismic isolation has advanced rapidly over the past decade, propelled by laboratory characterizations of sand-rubber and gravel-rubber mixtures, centrifuge tests demonstrating their protective performance, and shaking table experiments on medium-rise buildings founded on EPS bead-sand mixtures. Researchers have explored related variants, including soil mixed with recycled tire rubber, bitumen, and high-damping polyurethane, and have applied the concept to rural residences, highway embankments, and cut-and-cover utility tunnels. Analytical design models and fragility frameworks have followed, gradually building the engineering infrastructure needed to move GSI from promising research to routine practice.

What distinguishes the Turkish team’s contribution is its systematic treatment of two factors that interact: the spectral character of the earthquake and the geometry of the isolation layer. By coupling a frequency-classified ground motion set with a six-point thickness parametric study, the researchers generated a response surface that reveals where protection is most effective and where it saturates. Their analyses also confirm that the GSI system’s benefit is best understood as partial energy dissipation before the waves reach the foundation, a framing that positions the technology as a complement to, rather than a wholesale replacement for, structural isolation systems in high-consequence applications.

The authors note that their results should support the development of vibration control strategies aimed at improving the seismic resilience of structures, and that the data are expected to be useful for a better understanding of GSI applications in general. With no external funding and no competing interests declared, the study stands as a focused analytical contribution from a group with a sustained record in soil-structure interaction research. As cities in seismically active regions search for affordable, sustainable ways to protect ordinary buildings, the message from Gümüşhane is refreshingly concrete: bury a modest, two-to-three-meter cushion of rubber-enhanced soil beneath the foundation, recycle waste tires in the process, and expect the greatest gains in shielding structures from the low-frequency shaking that matters most, while resisting the temptation to assume that more isolation layer always means more protection.

Subject of Research: Seismic performance of buildings resting on geotechnical seismic isolation layers of varying thickness under earthquakes with different frequency content

Article Title: Effects of earthquake frequency content and isolation thickness on seismic behavior of a structure system resting on geotechnical seismic isolation layer

Article References: Ozturk, K. F., Cakir, T., & Araz, O. (2026). Effects of earthquake frequency content and isolation thickness on seismic behavior of a structure system resting on geotechnical seismic isolation layer. Bulletin of Earthquake Engineering. https://doi.org/10.1007/s10518-026-02658-8

Image Credits: AI Generated

DOI: 10.1007/s10518-026-02658-8

Keywords: geotechnical seismic isolation, earthquake engineering, rubber-soil mixtures, soil-structure interaction, frequency content, isolation thickness, seismic isolation, waste tire recycling, structural dynamics, vibration control, Bulletin of Earthquake Engineering, Gümüşhane University

The research, led by Guan Chen of the Earth Observatory of Singapore and the National University of Singapore, together with Siau Chen Chian, Michael Beer, and Shengji Wei, addresses a persistent gap in seismic hazard analysis. Engineers can already estimate how strong ground shaking will be at a given distance from an earthquake of a certain size using ground-motion prediction equations. What has been harder to quantify is the impulsive character of near-fault motion — how long the dominant pulse lasts, how large its velocity amplitude is, and how these quantities vary with the seismological setting. The new work links pulse parameters directly to magnitude, distance, and site stiffness, giving hazard analysts a physically grounded way to generate realistic near-fault ground motions for any scenario of interest.

The first technical challenge the team tackled was identification. Not every record close to a fault contains a clear pulse, and distinguishing pulse-like from non-pulse-like ground motions has traditionally relied on wavelet-based classification methods, most famously the approach introduced by Jack Baker in 2007. Many existing identification procedures, however, tend to extract a single type of pulse from a record, which can miss the richer structure of real near-fault motions. Records from large continental earthquakes frequently contain multiple pulses, arising from forward-directivity effects as the rupture front races toward the site, from fling-step associated with permanent tectonic deformation, or from constructive interference of seismic waves with basin geometry. A method that captures only one pulse type risks underrepresenting the destructive potential of the motion.

To overcome this limitation, the researchers developed a novel extraction procedure that integrates a parametric pulse model with the generalized continuous wavelet transform, or GCWT. The parametric model provides a mathematical description of the pulse shape, while the wavelet transform scans the velocity time series across scales and times to locate the energy concentration that corresponds to the pulse. By combining the two, the procedure can capture various types of pulses within a single record, preserving both the diversity and the accuracy of the extracted signals. The authors report that the pulses extracted by their method effectively match the pulse characteristics visible in the original records, a critical validation step before any statistical modeling can proceed.

Armed with this identification tool, the team mined the PEER NGA-West2 database, one of the largest curated collections of strong-motion recordings from shallow crustal earthquakes worldwide. Out of 21,222 records examined, 815 were identified as pulse-like ground motions. This carefully classified dataset forms the empirical backbone of the study. Each pulse-like record was decomposed into its pulse component and a residual component, and the parameters describing the pulse — including its period, amplitude, and the number of significant cycles — were tabulated alongside the corresponding earthquake magnitude, source-to-site distance, and Vs30 for each station.

The second major contribution is a set of empirical regression models that predict the pulse parameters from these three explanatory variables. The functional form of the models was developed with attention to the underlying physics: larger earthquakes produce longer rupture durations and hence longer pulse periods, pulses attenuate with distance as seismic energy spreads and is absorbed, and soft soil sites can amplify and lengthen the dominant velocity cycles relative to stiff rock. Model uncertainty was quantified through residual analysis, following the random-effects regression framework that has become standard in ground-motion modeling since the work of Abrahamson and Youngs in 1992. The proposed models were then validated against existing pulse models and against independent datasets not used in the calibration, providing confidence that the predictions generalize beyond the fitting sample.

A particularly valuable practical outcome of the study is a workflow for synthesizing near-fault broadband ground motions. The approach combines the empirical pulse model with a stochastic representation of the residual component — the high-frequency, incoherent part of the motion that remains after the coherent pulse is removed. Because the pulse and the residual are treated separately, the resulting artificial ground motions retain the distinctive impulsive features that govern structural response while simultaneously matching the spectral velocity and spectral acceleration of benchmark recordings across a broad frequency range. This two-component strategy echoes the spectral representation method in stochastic process simulation and offers a computationally efficient alternative to full physics-based rupture simulations, which remain expensive for routine hazard applications.

The implications for earthquake engineering are substantial. Previous research has demonstrated that near-fault pulses impose large deformation demands on flexible structures: moment-resisting frames subjected to pulse-like records accumulate damage differently than those subjected to ordinary shaking, and offshore wind turbines, tunnels, and seismically isolated buildings all show heightened vulnerability when the impulsive content of the motion is ignored. By providing pulse parameters conditioned on magnitude, distance, and site class, the new model allows analysts to construct scenario-consistent suites of near-fault motions without waiting for the next large earthquake to supply fresh recordings. The authors also note that the framework was informed by recent events, including the 2023 moment magnitude 7.8 Kahramanmaras earthquake in Turkey, whose near-fault recordings have become an important test case for pulse identification and simulation methods.

Accessibility is another notable feature of the work. The processed dataset, together with MATLAB code for identifying the optimal pulse in near-fault ground motions and for generating the empirical pulse model, has been released publicly through Zenodo, while the raw waveforms remain freely downloadable from the PEER NGA-West2 database. This open approach lowers the barrier for practicing engineers and researchers in seismically active regions to incorporate directivity and fling effects into their hazard and risk calculations. The study also acknowledges insightful discussions with Professor Jack W. Baker of Stanford University regarding pulse types and the functional form of the model, and it was supported by the Ministry of Education, Singapore, under the InVEST program for integrating volcano and earthquake science and technology.

For cities that sit directly above or beside active faults — from Los Angeles and Wellington to Istanbul and Kathmandu — the difference between ordinary shaking and a coherent velocity pulse can be the difference between repairable damage and collapse. By transforming decades of strong-motion recordings into a compact, predictive, and openly available model, this research moves the field closer to hazard assessments that reflect not just how hard the ground will shake, but how it will shake. As computational tools for seismic risk analysis grow more sophisticated, models of this kind provide the physically consistent input that engineers need to design structures capable of withstanding the sharpest blows an earthquake can deliver.

Subject of Research: Empirical modeling of near-fault velocity pulses in earthquake ground motion

Article Title: Empirical pulse model for near-fault ground motion considering magnitude, distance, and site characteristics

Article References: Chen, G., Chian, S. C., Beer, M., & Wei, S. (2026). Empirical pulse model for near-fault ground motion considering magnitude, distance, and site characteristics. Bulletin of Earthquake Engineering. https://doi.org/10.1007/s10518-026-02650-2

Image Credits: AI Generated

DOI: 10.1007/s10518-026-02650-2

Keywords: near-fault ground motion, velocity pulse, pulse-like records, NGA-West2, wavelet transform, seismic hazard, ground motion simulation, rupture directivity, fling-step, Vs30, earthquake engineering, Bulletin of Earthquake Engineering

The core problem the team set out to solve is one that plagues every data-driven surrogate model in engineering: error accumulation. Traditional physics-based constitutive models, which describe material and structural behavior through differential equations, are accurate but slow, often requiring substantial computational resources to simulate a single earthquake scenario. Data-driven surrogates, typically neural networks trained on the outputs of those expensive simulations, can produce predictions in milliseconds. The catch is that when a surrogate model is used for multi-step-ahead prediction, meaning it forecasts the structural state at the next time step and then feeds that forecast back in as input for the step after that, small inaccuracies compound. Over the duration of a long earthquake record, these errors snowball until the predicted response drifts far from reality, sometimes producing hysteretic loops that violate basic physical principles such as the conservation of energy.

The new framework attacks this problem from two directions simultaneously. The first is architectural: the backbone of the model is a hybrid Transformer-LSTM network. The Long Short-Term Memory component, a form of recurrent neural network, is designed to retain information over long sequences, making it well suited to tracking the evolving state of a structure as ground motion unfolds. The Transformer component, the architecture that underpins modern large language models, brings powerful attention mechanisms that can weigh the relevance of different moments in the shaking history when making a prediction. Together, the two components extract robust temporal features from the seismic input and the structural response history, allowing the network to directly predict the restoring force, the force the structure exerts in resistance to deformation, at each moment of the earthquake.

Architecture alone, however, cannot guarantee that a neural network behaves like a physical system. This is where the second innovation comes in: a consistency constraint based on hysteretic loop energy conservation, embedded directly into the loss function that guides training. During an earthquake, the area enclosed by a hysteretic loop represents the energy dissipated by the structure through yielding, friction, and other inelastic mechanisms. The researchers defined a time window and required that, within that window, the energy balance implied by the model’s predictions remain consistent with the physical energy dissipated in the corresponding hysteretic loop. Any prediction that would create or destroy energy out of nothing is penalized during training. The result is a network that is not merely fitting curves but is constrained to obey one of the most fundamental laws of physics, which in turn sharpens both its predictive accuracy and its physical plausibility.

The second line of attack addresses cumulative error propagation head-on through a cumulative error correction mechanism built on what the authors describe as a hybrid true-pseudo sample training strategy. In conventional training, a network learns to map true historical states to true future states. But at inference time, when the model is rolled forward through a long earthquake record, it must often consume its own predictions as inputs, states the training data never contained. This mismatch between training conditions and deployment conditions is a classic source of drift. The hybrid strategy exposes the network to both genuine samples and pseudo samples, states generated from the model’s own predictions during training, so that it learns to correct its own mistakes before they compound. The mechanism effectively teaches the surrogate to recognize and pull back toward physically meaningful trajectories even when it has wandered slightly off course.

Validation of the framework was comprehensive and systematic. The researchers first tested the model against two canonical mathematical descriptions of hysteretic behavior: the bilinear hysteretic model, a simplified representation of yielding systems, and the Bouc-Wen model, a smooth differential model widely used to capture the gradual stiffness degradation and pinching behavior of real structures. These benchmarks matter because they have known analytical behavior, allowing the team to quantify precisely how well the neural network reproduces the underlying physics. The framework was then implemented in both single-degree-of-freedom systems, which behave like a simple mass on a spring, and multiple-degree-of-freedom structural systems, which more realistically represent buildings with many interacting floors and components, all subjected to seismic ground motions.

Across these tests, the proposed framework demonstrated superior prediction accuracy compared with conventional data-driven approaches, along with enhanced extrapolation capability and robust generalization performance. Extrapolation capability is particularly significant in earthquake engineering, because the ground motions a real building will face in its lifetime may be stronger or of longer duration than anything in the training database. A surrogate that only interpolates within its training data is of limited use for safety assessment; one that can extend reliably beyond that data, while still respecting energy conservation, opens the door to rapid seismic performance evaluation across a much wider range of scenarios. The authors emphasize that these results highlight the framework’s potential as a physics-informed, data-driven approach for efficient seismic response prediction.

The broader context makes clear why this line of research has attracted intense interest. In recent years, deep learning has swept through structural engineering: LSTM networks have been used to predict the hysteresis of steel braces, convolutional and attention-based hybrids have been applied to long-period earthquake response, and physics-guided generative models have been proposed for damage prognosis in reinforced concrete bridge columns. Yet many of these models remain purely data-driven, with no explicit guarantee that their outputs obey conservation laws. The new study positions itself within a growing movement toward physics-informed machine learning, in which the equations and principles that engineers trust are woven into the fabric of the model rather than left for the data to rediscover. The authors also point to prior corrective training strategies for surrogate hysteretic models as an important precursor to their error correction mechanism, suggesting their contribution refines and extends an established idea with the addition of an explicit energy constraint.

The practical implications could extend well beyond the laboratory. Fast and reliable surrogates of nonlinear structural response are the engine behind many modern seismic risk tools, from fragility analysis of reinforced concrete frames to post-earthquake damage prediction for high-speed railway bridge systems, and from the design of seismic isolation devices to the safety assessment of trains running on bridges during shaking. If a surrogate can deliver accurate long-duration response predictions in a fraction of the time of a full nonlinear simulation, engineers could evaluate thousands of earthquake scenarios for a given structure, enabling probabilistic performance assessment at a scale that is currently impractical. The research was supported by the National Natural Science Foundation of China, the National Key Research and Development Program of China, the Japan Society for the Promotion of Science, and several provincial science foundations, reflecting the international and interdisciplinary nature of the effort.

The authors are careful to frame the current work as a foundation rather than a finished product. Their validation relied on idealized hysteretic models, bilinear and Bouc-Wen, which capture essential features of inelastic behavior but do not encompass the full complexity of real materials, including rebar buckling, strength deterioration under cyclic loading, or the asymmetric hysteresis of certain structural systems. The team explicitly identifies future investigations involving more complex hysteretic behaviors and engineering scenarios as the natural next step. Still, the central achievement stands: a neural network that predicts the violent, energy-dissipating dance of a structure during an earthquake, guided at every step by the conservation of energy and disciplined against its own drift. In a field where the difference between an accurate and a drifting prediction can shape decisions about life safety, that combination of speed, physics, and self-correction may prove to be exactly what earthquake engineering has been waiting for.

Subject of Research: Physics-guided deep learning for predicting hysteretic seismic response of structures with energy conservation constraints

Article Title: Physics-guided neural network for seismic hysteretic response prediction with energy conservation constraints and error correction

Article References: Shaohui, L., Lizhong, J., Wangbao, Z., Yuntai, Z., Lingxu, W., Yulin, F., & Tuo, Z. (2026). Physics-guided neural network for seismic hysteretic response prediction with energy conservation constraints and error correction. Bulletin of Earthquake Engineering. https://doi.org/10.1007/s10518-026-02657-9

Image Credits: AI Generated

DOI: 10.1007/s10518-026-02657-9

Keywords: physics-guided neural network, seismic response prediction, hysteretic behavior, energy conservation, Transformer-LSTM, cumulative error correction, Bouc-Wen model, earthquake engineering, surrogate modeling, structural dynamics, machine learning, Bulletin of Earthquake Engineering

A new study published in the Bulletin of Earthquake Engineering proposes a way to resolve that trade-off, and its central idea is disarmingly simple: give the earthquake something cheap and expendable to break. Researchers Min Jae Park of Pukyong National University in Busan, Ali Ghamari, Imran Karimi of Tabriz University, and Radhika Sridhar of Walailak University in Thailand have developed a hybrid precast concrete beam-column connection built around a replaceable I-shaped steel ductile link that functions as a structural seismic fuse. Like the fuse in an electrical circuit, the device is designed to absorb damage on behalf of the more valuable components around it, concentrating plastic deformation in a sacrificial element that can be unbolted and swapped out after a major event.

The mechanics of the system reflect a deliberate strategy of controlled damage. The steel link is bolted inside a steel-jacketed joint region at the intersection of the precast beam and column. During an earthquake, as the frame sways and the joint demands rotational capacity from the connected members, the I-shaped link yields in a controlled fashion, dissipating seismic energy through plastic deformation. Crucially, the design ensures that yielding is confined exclusively to the fuse itself. The precast beams, the columns, and the joint region are all shielded from the inelastic demands that would otherwise crack concrete, buckle reinforcement, and leave a structure permanently weakened or economically unrepairable. Once the shaking stops, the damaged link can be removed with ordinary tools and a new one installed, restoring the connection to its original capacity.

To understand how such a fuse should be proportioned, the research team carried out an extensive parametric and numerical study, anchored against experimental data to ensure the models reflected real structural behavior rather than numerical artifacts. Four key design variables came under scrutiny. The first was the ratio between the strength of the steel link and the strength of the concrete beam, denoted by the Greek letter psi, which governs whether the fuse or the surrounding concrete yields first. The second was the rho factor, capturing the effect of the relative resistance distribution within the connection. The third and fourth were the geometric properties of the I-shaped link itself: the thickness of its flanges and the depth of its cross-section, the two dimensions that most directly control how much bending resistance and deformation capacity the fuse can deliver before it is exhausted.

The results of the numerical campaign were strikingly consistent. Across the range of parameters examined, every model exhibited stable hysteretic behavior, the looping force-deformation signatures that engineers read as evidence of a structure absorbing and releasing seismic energy cycle after cycle without rapid deterioration. All models achieved moment capacities exceeding the plastic moment of the beam, meaning the fuse could reliably mobilize the full strength of the connection, and the system displayed minimal stiffness degradation, indicating that the connection did not progressively soften and loosen as the shaking continued. In seismic engineering, where degrading hysteresis loops often signal a connection heading toward collapse, this combination of stable loops and preserved stiffness is precisely the behavior a resilient system should show.

Perhaps the most consequential finding concerned which of the four design variables actually mattered most. Intuition might suggest that the strength ratio between the fuse and the concrete beam, psi, would dominate the response, since it determines where yielding occurs. The study found otherwise. The depth of the I-shaped link, h, exerted the strongest influence on the system’s behavior, outweighing the strength ratio, the rho factor, and the flange thickness. That result carries practical weight for designers: it means that tuning the depth of the sacrificial element is the most powerful lever available for shaping how the connection performs, a conclusion that was not obvious before the parametric study was run and one that could redirect how future fuses are detailed.

Beyond identifying the dominant parameter, the researchers distilled their findings into proposed design equations for the system, giving practitioners a quantitative route from target performance to fuse dimensions. Design equations of this kind are the bridge between a promising laboratory concept and a buildable technology, because they allow engineers to size the link so that it yields before the surrounding precast elements, sustains the large deformations expected in a design-level earthquake, and retains enough residual capacity to protect the joint through the full duration of strong ground motion. The study’s grounding in established seismic frameworks, including references to modern minimum design load provisions and seismic provisions for structural steel buildings, situates the proposal within the codes that already govern practice.

The motivation for this line of research is written in the damage surveys of recent disasters. Investigations following the February 2023 Kahramanmaras earthquake sequence in Turkey documented widespread failures of reinforced concrete and precast construction, with brittle connections and inadequate detailing cited among the recurring deficiencies. Earlier events, notably the 2011 Christchurch earthquake in New Zealand, exposed how conventionally detailed reinforced concrete frames can suffer damage so extensive that repair becomes uneconomical, forcing demolition of buildings that technically did not collapse. Those experiences have pushed the international research community toward a resilience paradigm that goes beyond life safety: structures should not merely stand up during an earthquake but should emerge from it repairable, functional, and quickly returnable to service.

Replaceable fuse technology has become one of the most active fronts in that paradigm shift, with researchers developing damage-control joints, bio-inspired hinges, artificial controllable plastic hinges, and self-centering connections for both cast-in-place and precast frames. What distinguishes the new study is its integration of the fuse concept into a hybrid precast connection that preserves the construction speed advantages of precast systems while solving their historical connection problem. The bolted arrangement inside a steel-jacketed joint means the fuse is not cast into the concrete or welded into place, so replacement is a matter of unbolting rather than cutting, chipping, and recasting. For building owners and city planners, that distinction translates directly into downtime: a connection repaired in days rather than months keeps schools open, hospitals running, and businesses operating after a quake.

The work, supported by grants from the National Research Foundation of Korea and the Korea Agency for Infrastructure Technology Advancement, along with facilities provided by Walailak University, arrives at a moment when the global building stock in earthquake-prone regions is expanding fastest precisely where seismic risk is highest. Precast construction will remain attractive to developers for its speed and economy, and the question is not whether it will be used but whether it will be used safely. By demonstrating through validated numerical modeling that a bolted, replaceable, ductile steel fuse can deliver stable hysteretic performance, protect the primary structure, and be tuned through a single dominant geometric parameter, the researchers have offered the industry a concrete, and constructible, answer. The next steps toward widespread adoption will involve experimental validation at full scale and codification of the proposed design equations, but the study makes a compelling case that the weakest link in precast construction can be redesigned into its strongest feature: a sacrificial component that takes the hit so the building does not have to.

Subject of Research: Seismic-resilient precast concrete beam-column connections with replaceable ductile steel fuses

Article Title: Towards resilient precast concrete frame featuring a hybrid system with replaceable ductile steel fuses

Article References: Park, M. J., Ghamari, A., Karimi, I., & Sridhar, R. (2026). Towards resilient precast concrete frame featuring a hybrid system with replaceable ductile steel fuses. Bulletin of Earthquake Engineering. https://doi.org/10.1007/s10518-026-02668-6

Image Credits: AI Generated

DOI: 10.1007/s10518-026-02668-6

Keywords: precast concrete, seismic fuse, ductile steel link, beam-column connection, earthquake engineering, hysteretic behavior, replaceable plastic hinge, structural resilience, parametric study, stiffness degradation, repairable structures, Bulletin of Earthquake Engineering

Prefabricated reinforced concrete construction occupies a distinctive place in structural engineering. Unlike cast-in-place buildings, whose columns and beams are monolithically poured, precast structures are assembled from factory-produced elements joined on site. This makes them fast and economical to build, but it concentrates seismic vulnerability in the connections. In the classic Turkish precast industrial building, roof girders rest on column corbels, typically through dowel bars and elastomeric bearing pads, and the entire lateral load path depends on how well these joints hold together when the ground lurches. The 2023 Kahramanmaraş earthquake sequence, with its pulse-like near-fault motions and unusually high vertical accelerations, tested those joints as severely as any event in Turkish history.

The research team began with field investigations in the affected region, documenting damage patterns across prefabricated buildings exposed to the twin shocks. Their reconnaissance identified a recurring catalogue of construction deficiencies: inadequate dowel detailing at girder-corbel connections, missing elastomeric bearing pads, substandard grout applications, and insufficient confinement reinforcement in columns and joints. Each of these defects, individually modest in appearance, proved capable of triggering or accelerating structural failure. Where bearing pads were absent, girders pounded directly against concrete corbels, crushing the bearing surfaces and losing their ability to accommodate the relative displacements that near-fault shaking imposes. Where dowels were poorly anchored or under-reinforced, the connections that should have tied roof girders to columns simply gave way.

These observations align with a long history of lessons from Turkish earthquakes. Precast structures were damaged in the 1998 Ceyhan earthquake, the 1999 Kocaeli earthquake, the 2011 Van earthquake, and the 2020 Sivrice earthquake, and in each event the same weak points surfaced: connections, corbels, and the detailing that modern codes require but field practice does not always deliver. What distinguishes the new study is that it does not stop at cataloguing damage. It converts the field evidence into quantitative fragility models, the statistical machinery that engineers use to estimate the probability that a structure will exceed a given damage state at a given level of ground shaking intensity.

Fragility analysis works by subjecting numerical models of a structure to suites of ground motion records and tracking how often a governing limit state, such as the onset of significant connection damage or loss of lateral load capacity, is exceeded as shaking intensity increases. The team built detailed nonlinear models of representative reinforced concrete prefabricated buildings and ran them through ground motions representative of the Kahramanmaraş sequence, including records with the velocity pulses and strong vertical components characteristic of near-fault sites. The resulting fragility curves provide a probabilistic portrait of vulnerability, allowing engineers to compare design variants on a common, defensible footing rather than relying on anecdote alone.

The single most striking quantitative finding concerns the roof girder-to-corbel connection. When the dowels connecting girders to columns were bolted, the seismic resilience of the structure improved dramatically: the median ground motion intensity at which the governing limit state was exceeded nearly doubled compared with structures relying on unbolted dowel connections. In practical terms, a building with bolted dowel connections could withstand roughly twice the shaking intensity before reaching its critical damage threshold. That is not an incremental improvement; it is the difference between a structure that survives a near-fault event and one that does not, achieved through a connection detail that costs comparatively little to implement.

The study also examined the role of infill walls, the masonry or precast panels that fill the bays between columns. In general, infill walls improved seismic resistance, stiffening the frames and sharing lateral load that would otherwise concentrate entirely on the columns. But the analysis revealed a crucial caveat: the benefit depended heavily on the integrity of the connections between the walls and the surrounding frame. Where those connections were robust, the walls acted as effective seismic fuses and load-sharing elements. Where the connections were poor, the walls detached early, their contribution vanished, and in some scenarios the falling panels introduced additional hazards. The lesson is that infill walls are not a passive benefit that can be assumed; they are only as good as the detailing that ties them into the structural system.

Near-fault effects emerged as a decisive amplifier of all these vulnerabilities. Earthquakes that rupture directly beneath or very close to a site produce ground motions with forward directivity, meaning a long-period velocity pulse arrives with much of the fault’s slip concentrated in a single large cycle of motion. The Kahramanmaraş events, including documented episodes of supershear rupture, delivered exactly this kind of pulse-like loading, along with vertical accelerations strong enough to degrade the friction and bearing capacity of simply supported precast elements. For connections already weakened by missing pads or deficient dowels, the combination of horizontal pulses and vertical acceleration was punishing. The study’s numerical results make clear that fragility assessments for precast buildings in near-fault zones must explicitly account for these motion characteristics rather than relying on generic record sets.

From these findings the authors draw a clear retrofitting agenda for the existing stock of reinforced concrete prefabricated structures. Priority measures include upgrading connection details, particularly bolting dowel connections at girder-corbel joints; adding elastomeric bearing pads where they are missing; and installing properly designed precast infill walls with reliable connections. Beyond the physical interventions, the study emphasizes the need for clear design guidelines and rigorous field assessment protocols so that existing buildings, especially in regions exposed to near-fault seismicity, can be systematically evaluated and reinforced before the next earthquake rather than after. The authors note that implementing these strategies would substantially enhance the seismic resilience of the precast building stock, reducing potential future human and economic losses.

The broader significance of the work extends beyond Türkiye. Precast industrial construction is common across seismic regions worldwide, from the Mediterranean to the Americas, and the failure modes documented after Kahramanmaraş echo those observed after the 2012 Emilia earthquakes in Italy, the 1994 Northridge earthquake in California, and the 1995 Kobe earthquake in Japan. The Turkish study adds a quantitative dimension to that international record, demonstrating with fragility curves just how much performance hinges on a handful of connection details. For engineers, the message is disarmingly simple: in prefabricated construction, the earthquake finds the joints. Bolting a dowel, seating a bearing pad, or grouting a connection properly may look like minor line items in a construction budget, but the difference they make, roughly a doubling of the shaking a building can survive, is the kind of margin on which lives and livelihoods depend when the fault finally slips.

Subject of Research: Seismic fragility and construction deficiencies of reinforced concrete prefabricated buildings in the 2023 Kahramanmaraş earthquakes

Article Title: Seismic performance assessment of reinforced concrete prefabricated structures during the 2023 Kahramanmaraş earthquakes: fragility analysis and construction deficiency evaluation

Article References: Ti̇murağaoğlu, M. Ö., Hakan, Ö., Bayram, A. H., & Li̇vaoğlu, R. (2026). Seismic performance assessment of reinforced concrete prefabricated structures during the 2023 Kahramanmaraş earthquakes: fragility analysis and construction deficiency evaluation. Bulletin of Earthquake Engineering. https://doi.org/10.1007/s10518-026-02712-5

Image Credits: AI Generated

DOI: 10.1007/s10518-026-02712-5

Keywords: prefabricated concrete, Kahramanmaraş earthquakes, fragility analysis, seismic performance, dowel connections, corbel connection, elastomeric bearing pads, infill walls, near-fault ground motion, retrofitting, East Anatolian Fault, Bulletin of Earthquake Engineering

The research, led by Xiaohui Yu, Zenghui Li, Zihan He, Kuangyu Dai and Feng Fu, with affiliations spanning Guilin University of Technology, Zhengzhou University and City, University of London, focuses on the hysteretic behavior of reinforced concrete columns. Hysteresis describes the looping force–displacement curves a column traces as it is pushed back and forth past its elastic limit. These loops encode everything engineers need to know about a column’s energy dissipation, stiffness degradation and strength deterioration, but measuring them for real damaged structures is slow, expensive and often impossible after a disaster.

To build a foundation for their predictive models, the team first assembled a comprehensive database of 1,053 reinforced concrete column specimens tested under cyclic loading. For each column, the hysteretic response was simulated using the modified Ibarra–Medina–Krawinkler (I-M-K) model, a phenomenological framework widely used in seismic collapse assessment. The I-M-K model represents a column’s backbone curve — the envelope of its strength and stiffness — together with rules for cyclic deterioration, capturing how repeated inelastic cycles progressively erode yield strength, unloading stiffness, and post-capping behavior.

The central innovation lies in a two-stage simulation strategy designed to mimic what an earthquake actually does to a structure. In the first stage, a partial loading history drawn from the experimental data is applied to each intact column, producing a wide range of initial damage states, from hairline cracking to severe strength loss. In the second stage, the complete loading history is applied to these now-damaged columns, generating the full hysteretic response of a structure that has already been through a mainshock. This approach effectively turns one experimental record into many, allowing the researchers to explore the continuum between pristine and heavily damaged states without physically breaking hundreds of additional specimens.

From the simulated responses of the damaged columns, the researchers identified the backbone and cyclic deterioration parameters of the modified I-M-K model. By comparing the backbone parameters of damaged columns with those of their intact counterparts, they quantified damage-induced reduction factors, or DRFs, for key quantities including yield strength, elastic stiffness, strain hardening ratio, capping strength, and the chord rotation of the softening stage. These factors express, in precise numerical terms, how much of a column’s original capacity survives a given level of earthquake damage.

With the database of DRFs and deterioration parameters in hand, the team trained six different machine learning models to predict these values directly from a column’s initial damage state and its design parameters — inputs such as axial load ratio, longitudinal and transverse reinforcement ratios, concrete compressive strength, stirrup spacing, shear span-to-depth ratio, and cross-sectional dimensions. Rather than relying on a single arbitrary train-test split, the models were trained and tested across 1,000 random splits, a rigorous protocol that guards against lucky partitions and gives a robust picture of each algorithm’s true performance.

The verdict was clear: XGBoost, the gradient-boosted decision tree algorithm that has become a favorite in engineering applications, exhibited the best performance in predicting the hysteretic behavior of damaged columns. XGBoost builds an ensemble of decision trees sequentially, with each new tree correcting the errors of the previous ones, making it particularly adept at capturing the nonlinear interactions between design variables and damage states that govern structural response. To test that the model was not simply memorizing its training data, the researchers also evaluated it on three reinforced concrete column specimens outside the original database, examining its general applicability to unseen cases.

Crucially, the study does not treat its model as a black box. Using SHapley Additive exPlanations, or SHAP, a technique borrowed from cooperative game theory that attributes each prediction to the contributions of individual input features, the researchers interrogated what their model had learned. The analysis indicated that initial damage is the most influential feature governing the reduced hysteretic parameters — an intuitive but now quantitatively confirmed result, since the severity of pre-existing damage directly controls how much strength and stiffness remain for subsequent loading.

The practical implications extend well beyond the laboratory. After a damaging earthquake, engineers must rapidly decide whether a building is safe for occupancy, whether it needs retrofitting, or whether it should be demolished. Current post-earthquake assessment practice often relies on simplified damage indices, such as the Park–Ang damage index, and conservative assumptions that can lead to unnecessary closures or, worse, underestimated risk. A trained surrogate model like the one developed here could take measurable column properties and an estimate of sustained damage and return, in seconds, a full prediction of the residual hysteretic envelope — feeding directly into aftershock fragility analysis and resilience planning for entire building stocks.

The work also fits into a broader movement in earthquake engineering toward machine-learning-assisted seismic assessment, with recent studies applying similar methods to fragility estimation, drift capacity prediction, and parameter identification for nonlinear structural models. By releasing their column database as supplementary material and making the source code openly available on GitHub, the authors have lowered the barrier for other researchers to build on the approach. As cities in seismic regions face aging infrastructure and increasing exposure, tools that translate raw data into rapid, explainable predictions of residual capacity may become as essential to post-earthquake response as the seismometers that record the shaking itself.

Subject of Research: Machine learning prediction of the residual hysteretic behavior of post-earthquake damaged reinforced concrete columns

Article Title: Hysteretic behavior prediction of post-earthquake damaged reinforced concrete columns using machine learning

Article References: Yu, X., Li, Z., He, Z., Dai, K., & Fu, F. (2026). Hysteretic behavior prediction of post-earthquake damaged reinforced concrete columns using machine learning. Bulletin of Earthquake Engineering. https://doi.org/10.1007/s10518-026-02704-5

Image Credits: AI Generated

DOI: 10.1007/s10518-026-02704-5

Keywords: machine learning, XGBoost, reinforced concrete columns, hysteretic behavior, post-earthquake damage, seismic assessment, Ibarra-Medina-Krawinkler model, damage-induced reduction factors, SHAP, aftershock resilience, structural engineering, Bulletin of Earthquake Engineering

The method applies to a class of buildings that dominates urban landscapes across the seismic world: regular reinforced concrete structures of two to eight stories, with story heights not exceeding four meters, and without significant structural irregularities. These are the apartment blocks, schools, offices and mixed-use buildings that line the streets of Istanbul, Athens, Santiago, Manila and countless other cities sitting near active faults. The procedure covers both frame-only systems, in which moment-resisting frames carry all lateral loads, and dual systems that combine frames with structural walls. By targeting precisely this building stock, the researchers have aimed their tool at the scale of the problem where improved preliminary design can save the most lives.

What makes the approach remarkable is its economy of input. Rather than demanding a complete structural model, the simplified method requires only estimated gravity loads, column tributary areas, the number of stories, story heights, plan areas, and the short-period design spectral acceleration for the site. From these basic quantities, the procedure uses fundamental mechanics of materials and minimum reinforcement requirements to proportion beams, columns and walls so that the resulting structure achieves adequate strength, stiffness and ductility at both the member level and the system level. In other words, the method embeds the core lessons of decades of earthquake engineering, capacity design principles and ductile detailing into a streamlined calculation sequence that a practicing engineer can complete in minutes rather than days.

The intellectual lineage of the procedure stretches back decades. Uğur Ersoy, one of Turkey’s most influential reinforced concrete researchers, developed the original formulation, which drew on international experience with simplified design guides, including the American Concrete Institute’s simplified design documents, Japanese seismic provisions, and the empirical wall-index observations of Shiga and colleagues after Japanese earthquakes. That heritage matters because the method is not an abstract exercise; it distills field evidence about which buildings survived past earthquakes and why. Buildings with sufficient walls, well-proportioned members and sensible proportions have repeatedly performed better in Chile, Japan and Turkey, and the new procedure translates those observations into explicit design rules for the modern code environment.

The real test of any simplified method is whether its output can survive scrutiny by the most demanding analysis tools available. The research team put 27 buildings, 11 frame-only structures and 16 dual frame-wall systems, through nonlinear static pushover analyses. Every one of these buildings was designed solely with the simplified method, using realistic and hypothetical configurations representative of actual practice. The pushover analyses pushed each structure laterally until its components reached defined performance limits, allowing the researchers to evaluate performance levels and shear demand-to-capacity ratios for every beam, column and wall according to ASCE 41-23, ACI 369.1-22 and ACI 318-25, three of the most authoritative standards in American structural engineering practice.

The results are striking. Under the design-basis earthquake, columns and walls in all of the evaluated buildings achieved at least the life safety performance level, the standard that ensures structural elements may be damaged but remain able to protect occupants. Beams, which are intentionally detailed to yield and dissipate energy before more critical members do, ranged between life safety and collapse prevention, exactly the hierarchy that modern capacity design seeks to enforce. Shear capacity proved adequate for nearly all members, with the only exceptions being a few short-span beams that fell outside the method’s stated applicability limits, a finding that reinforces the importance of respecting the boundaries within which any simplified tool is valid.

Comparisons with designs produced through the full TBER 2018 code route revealed another important property: the simplified method provides an acceptable level of conservatism. That conservatism manifests primarily in member dimensions rather than in reinforcement quantities, meaning the procedure tends to produce somewhat larger columns, beams and walls while keeping steel demands reasonable. For practitioners, this is a reassuring outcome. It suggests the method erringly errs on the side of robustness, giving early-stage designs a comfortable margin that will be refined, but not radically overhauled, in the final code-compliant design phase that follows.

The urgency behind this work is impossible to separate from recent seismic tragedy. The February 2023 Kahramanmaraş earthquake doublets in Türkiye, with magnitudes of 7.8 and 7.6, caused catastrophic damage to thousands of reinforced concrete buildings and prompted a wave of reconnaissance studies documenting failures that better preliminary design could have prevented. The study’s reference list is punctuated with field reports from that disaster and from earlier Turkish earthquakes in Kocaeli, Bingöl and Van, alongside lessons from the 1985 Chile and 1995 Kobe events. This context gives the research its emotional weight: every paragraph of the validation effort is ultimately about preventing the next collapse, particularly in a country where millions of people live in buildings of exactly the type the method addresses.

The researchers are careful to position the tool correctly within the design workflow. The simplified method is a preliminary design procedure, not a substitute for final structural design. It dispenses with elaborate analysis at the concept stage, when architects and engineers are negotiating layouts, column grids and wall locations, and it guarantees instead a minimum acceptable level of seismic performance from the very first sketch. The final code-compliant design, with its full three-dimensional modeling, modal response spectrum or time-history analysis, and detailed reinforcement design, is performed subsequently. By front-loading seismic competence into the earliest decisions, the method prevents the most dangerous failure mode of the design process itself: the discovery, late in the project, that the chosen architecture cannot be made seismically sound without painful and expensive redesign.

The authors conclude that the simplified method offers a practical, intuitive, rapid and reliable tool for the preliminary seismic design of regular low- to medium-rise reinforced concrete buildings. In an era when performance-based design has become increasingly sophisticated and computationally demanding, there is something quietly revolutionary about a procedure that argues for simplicity as a safety feature. Complex codes are only as effective as the practitioners who apply them correctly, and the gap between cutting-edge analysis and everyday practice is where many seismic vulnerabilities are born. By closing that gap with a method grounded in mechanics, validated against modern performance standards, and now written into a national seismic code, this research demonstrates that sometimes the most powerful engineering innovation is the one that makes doing the right thing the easiest thing to do. For the residents of eight-story apartment buildings from Istanbul to wherever the next great earthquake will strike, that simplicity may prove to be the difference between a shaken building and a collapsed one.

Subject of Research: Simplified preliminary seismic design of low-to-medium rise reinforced concrete buildings

Article Title: A simple preliminary seismic design procedure for low-to-medium rise reinforced concrete buildings

Article References: Akalp, S., Orakçal, K., İlki, A., Luş, H., Gülkan, P., & Ersoy, U. (2026). A simple preliminary seismic design procedure for low-to-medium rise reinforced concrete buildings. Bulletin of Earthquake Engineering. https://doi.org/10.1007/s10518-026-02696-2

Image Credits: AI Generated

DOI: 10.1007/s10518-026-02696-2

Keywords: seismic design, reinforced concrete, earthquake engineering, preliminary design, TBER 2018, ASCE 41-23, pushover analysis, dual systems, moment-resisting frames, life safety, capacity design, Bulletin of Earthquake Engineering

For decades, seismic hazard assessment in most parts of the world has concentrated on horizontal ground motion, driven by the observation that lateral forces are usually the primary cause of structural collapse. Yet engineers have increasingly recognized that vertical shaking can impose severe axial demands on columns, beams, and connections, particularly in reinforced concrete frames, bridges, and base-isolated structures. Laboratory testing and post-earthquake investigations have repeatedly shown that reinforced concrete columns subjected to combined horizontal and vertical accelerations lose load-carrying capacity faster than those facing lateral motion alone, and that vertical ground motion has been implicated in damage to historical structures and modern buildings alike. Until now, El Salvador’s building codes and hazard maps have lacked a rigorous, nationally calibrated basis for quantifying that vertical threat.

The new work presents time-independent probabilistic seismic hazard maps expressed in terms of vertical peak ground acceleration and spectral ordinates at periods of 0.2 and 1 seconds, computed for 5 percent of critical damping. These values were produced for rock site conditions and flat topography across five return periods: 50, 95, 475, 975, and 2475 years. The return-period framework mirrors the conventions used in modern design standards, allowing engineers to select ground-motion intensities appropriate to the importance and intended lifespan of a structure. A 475-year return period, corresponding to roughly a 10 percent probability of exceedance in 50 years, is the traditional benchmark for ordinary buildings, while the rarer 2475-year event informs the design of critical facilities such as hospitals and emergency centers.

To construct the hazard models, Salazar employed two complementary approaches: the classical area source method and the smoothed seismicity method. The area source approach divides a region into discrete zones assumed to share uniform seismicity characteristics, a technique rooted in Cornell’s foundational 1968 formulation of engineering seismic risk analysis. The smoothed seismicity method, pioneered by Gordon Woo in the 1990s, dispenses with rigid zonation boundaries and instead spreads earthquake occurrence spatially using kernel functions, letting the historical record itself shape the hazard landscape. Using both methods within a logic tree framework allows the analysis to capture epistemic uncertainty, the uncertainty arising from incomplete scientific knowledge about where and how frequently earthquakes occur.

The seismicity evaluation draws on a homogenized earthquake catalog spanning nearly five centuries, from 1528 to 2023, with moment magnitudes ranging from 5.0 to 8.1. Bringing nearly 500 years of historical and instrumental records into a consistent magnitude scale is one of the most labor-intensive aspects of hazard analysis in developing countries, where early accounts may consist only of damage descriptions in colonial archives. From this catalog the study derived classical Gutenberg-Richter frequency-magnitude relationships, which describe the predictable inverse relationship between earthquake size and occurrence rate, as well as average kernel bandwidth distances, a measure of the typical spacing among epicenters of earthquakes of the same size that parameterizes the smoothed seismicity calculations.

A distinctive strength of the study lies in its empirical testing of vertical ground-motion prediction equations against actual accelerometer recordings from El Salvador itself. The candidate equations were evaluated against data from the two destructive earthquakes of 2001: the January 13 event of magnitude 7.7, which ruptured within the Cocos plate subduction zone offshore, and the February 13 event of magnitude 6.5, which struck in the volcanic chain zone where shallow crustal faults cut across the densely populated interior. Both earthquakes caused catastrophic losses, and their contrasting tectonic settings make them ideal calibration points for distinguishing how subduction interface and upper-crustal earthquakes transmit vertical energy to the surface. Salazar also accounted for hanging-wall effects, the amplification of shaking that occurs at sites located above the up-dip edge of a dipping fault rupture, which can substantially elevate ground motions at near-fault locations.

The weighting of competing ground-motion models in the logic tree was informed directly by how well each vertical prediction equation reproduced the observed Salvadoran recordings, rather than being assigned arbitrarily or borrowed wholesale from other regions. This data-driven calibration matters because vertical-to-horizontal spectral ratios vary widely across tectonic regimes, and models developed for Japan, Italy, Taiwan, or the Mediterranean do not necessarily transfer cleanly to Central America’s unique combination of a rapidly subducting oceanic plate and an active volcanic arc. By anchoring the model selection to local data, the study reduces one of the largest sources of uncertainty in vertical hazard estimates.

Among the study’s most practical outputs are proposed relations between horizontal and vertical map accelerations, expressed across all the return periods considered. These vertical-to-horizontal ratios provide an efficient bridge for practicing engineers: instead of requiring new vertical hazard computations for every site, designers can derive vertical design forces directly from the horizontal hazard values already in use, scaled by the locally calibrated ratios. Given that international design provisions, including the American Society of Civil Engineers’ ASCE 7-22 standard, increasingly demand explicit treatment of vertical seismic effects, such locally derived conversion factors are precisely what national code committees need to modernize requirements without embarking on a parallel hazard analysis from scratch.

The implications extend beyond structural engineering practice. El Salvador’s seismic vulnerability was starkly demonstrated in 1986, when the San Salvador earthquake destroyed thousands of buildings, and again in 2001, when the two major quakes within a month devastated communities already struggling with recovery. Recent geodetic work using GNSS and InSAR has continued to map the accumulating tectonic deformation across the country, underscoring that the forces driving the hazard remain fully active. Regional hazard models developed for sovereign parametric insurance also depend on the kind of robust, probabilistic ground-motion characterization this study provides, meaning the new vertical maps could ultimately inform not only building design but financial instruments that transfer catastrophe risk at the national scale.

For a country that sits atop one of the planet’s most active seismic engines, the message of this research is clear: the ground does not only move sideways, and the engineering community must plan for the full three-dimensional character of earthquake shaking. By combining a five-century earthquake catalog, dual seismicity modeling methods, empirically tested vertical ground-motion equations validated against Salvadoran strong-motion records, and practical hazard maps spanning return periods from 50 to 2475 years, the study gives El Salvador a technical foundation that few nations of its size possess. The work was supported by research grants from the Catholic University of El Salvador and made use of Woo’s KERFRACT Fortran code for smoothed seismicity, and it stands as a template for how data-scarce, high-hazard countries can leverage both historical archives and modern instrumental networks to quantify the risks beneath their feet.

Subject of Research: Probabilistic seismic hazard mapping of vertical earthquake ground motion components in El Salvador

Article Title: Seismic hazard maps for El Salvador: the vertical component of motion

Article References: Salazar, W. (2026). Seismic hazard maps for El Salvador: the vertical component of motion. Bulletin of Earthquake Engineering. https://doi.org/10.1007/s10518-026-02665-9

Image Credits: AI Generated

DOI: 10.1007/s10518-026-02665-9

Keywords: seismic hazard, El Salvador, vertical ground motion, probabilistic seismic hazard analysis, ground-motion prediction equations, smoothed seismicity, subduction zone, earthquake catalog, logic tree, return period, vertical-to-horizontal ratio, Bulletin of Earthquake Engineering