The core of the problem lies in a mismatch between what traditional seismic metrics measure and what actually breaks in an earthquake. For decades, engineers have gauged ground motion severity using quantities such as peak ground acceleration, or PGA, and correlated them with the inter-story drift ratio, the sideways deformation between adjacent floors. That pairing works reasonably well when the question is whether the structural skeleton will collapse. But the modern philosophy of seismic design, increasingly framed around functional recovery, asks a different question: after the shaking stops, can the building still be used? Answering that question means caring about nonstructural elements, from elevator machinery to medical equipment, and those components respond not to drift but to the acceleration and velocity of the floor slabs they sit on.

This distinction matters enormously in super-tall buildings, where the dynamic behavior is dominated by higher vibration modes. A building with a fundamental period of several seconds does not simply sway back and forth as a single unit; its floors oscillate in complex patterns, and accelerations can amplify dramatically at upper levels in ways that bear little relationship to the peak acceleration recorded at the ground surface. Scaling ground motions to match PGA, a common practice in time-history analysis, therefore produces a poor and inefficient predictor of floor-level demands. Engineers compensating for this scatter must run many more analyses, each computationally expensive for a detailed model of a 489-meter tower, driving up the cost and time of every performance assessment.

Cao and Qu’s solution is a scalar intensity measure rooted in the spectral acceleration of the ground motion, but weighted and combined in a way that explicitly reflects both peak floor acceleration and peak floor velocity demands. Spectral acceleration describes the maximum response of a single-degree-of-freedom oscillator of a given period to a ground motion, and averaged spectral quantities have proven powerful for collapse assessment in prior research. The authors extended this idea by calibrating the key parameters of their measure against an enormous body of simulation data: approximately 100,000 time-history analyses of building models whose fundamental periods ranged from one second to ten seconds, covering the full span of tall and super-tall structural behavior.

The calibration campaign is what gives the new measure its teeth. By regressing floor-level demands against candidate intensity measures across this vast library of ground-motion-and-building combinations, the researchers could identify the spectral weighting that minimizes the dispersion between predicted and actual demands. In the vocabulary of performance-based earthquake engineering, the resulting measure exhibits high efficiency, meaning less scatter in the demand prediction, and sufficiency, meaning it captures the demand well regardless of the magnitude, distance, or spectral character of the earthquake that produced it. These two properties are the gold standards for any intensity measure intended for probabilistic seismic demand analysis, because they determine how many ground motion records an analyst must run to obtain a trustworthy estimate of risk.

The efficiency gains reported in the study are striking. When the proposed intensity measure was tested against a 489-meter super-tall building archetype, a structure representative of the tallest class of towers now common in Chinese metropolitan skylines, only seven ground motion records were needed to achieve a stable average response. Conventional scaling based on peak ground acceleration required twenty-three records to reach the same stability, a 70 percent reduction in the number of analyses. For a nonlinear model of a super-tall building, where a single time-history simulation can consume hours of computation, that reduction translates directly into days or weeks saved on every vulnerability study, and into the practical feasibility of running the many analyses required by modern performance-based design codes.

To demonstrate the practical payoff, the authors applied their intensity measure to a seismic vulnerability assessment of rocking freestanding indoor contents, the unanchored furniture, cabinets, and equipment that populate real floors and are notorious for sliding and overturning during earthquakes. Freestanding bodies rock and topple in response to both the acceleration and the velocity of the floor beneath them, which is precisely why a measure capturing both quantities outperforms acceleration-only or drift-based alternatives. The study builds on a long line of research into rigid-body overturning, from classic criteria for earthquake-induced rocking through recent experimental work on electrical cabinets and hospital equipment, and shows how a better ground-motion descriptor flows through the entire fragility pipeline to yield more reliable estimates of content damage.

The implications reach beyond the laboratory into codes and practice. Performance-based seismic design standards, including the FEMA P-58 framework in the United States and a family of Chinese specifications for tall buildings, increasingly demand quantified predictions of nonstructural damage and downtime. An intensity measure that targets the demands actually experienced by nonstructural components gives engineers a sharper instrument for those calculations, and its computational efficiency makes routine fragility assessment of super-tall towers far more tractable. The work also aligns with a broader trend in earthquake engineering: rather than treating the building as an isolated skeleton, designers are learning to evaluate the full functional system, structure, contents, and occupants together, because a building that stands but cannot operate has failed the recovery test.

The research, funded by the Natural Science Foundation of China and the Institute of Engineering Mechanics of the China Earthquake Administration, arrives at a moment when super-tall construction and seismic risk are converging in densely populated regions. As cities push towers ever higher, the floors near the top will experience acceleration demands that ground-level instruments cannot foreshadow, and the contents of those floors, from data centers to emergency supplies, will determine how quickly a shaken city returns to normal. By recalibrating the language engineers use to describe earthquake intensity around the quantities that govern nonstructural damage, Cao and Qu offer a deceptively simple but consequential upgrade: fewer simulations, tighter predictions, and a clearer path to buildings that not only survive great earthquakes but keep working afterward.

Subject of Research: A spectral-acceleration intensity measure for predicting peak floor acceleration and velocity demands in super-tall buildings

Article Title: A spectral-acceleration intensity measure for peak floor acceleration and velocity demands in super-tall buildings

Article References: Cao, Y., & Qu, Z. (2026). A spectral-acceleration intensity measure for peak floor acceleration and velocity demands in super-tall buildings. Bulletin of Earthquake Engineering. https://doi.org/10.1007/s10518-026-02695-3

Image Credits: AI Generated

DOI: 10.1007/s10518-026-02695-3

Keywords: earthquake engineering, intensity measure, super-tall buildings, peak floor acceleration, peak floor velocity, nonstructural elements, spectral acceleration, time-history analysis, seismic vulnerability, performance-based design, functional recovery, fragility assessment