The review focuses on transmission tower-line systems, often abbreviated TTLS, which are not simple structures to analyze. A transmission line is a coupled system in which slender, flexible cables interact with comparatively stiff lattice towers through insulator strings and fittings. When ice forms unevenly on a conductor, or when wind causes the cables to oscillate, the resulting forces are transmitted dynamically to the towers, which can vibrate, buckle, or shed their loads suddenly. Dynamic response analysis, the discipline concerned with calculating how these structures move, deform, and fail under time-varying loads, is therefore indispensable for explaining failure mechanisms and for guiding disaster mitigation strategies. The authors organize the field into four broad families of methods: analytical and mechanics-based approaches, numerical simulation methods, stochastic and statistical techniques, and emerging methods built on artificial intelligence.

Analytical and mechanics-based methods represent the classical foundation of the field. These approaches rely on simplified physical models, such as treating a conductor as a catenary cable or representing a tower as a beam or truss framework, and then deriving equations of motion that can be solved to estimate stresses, deflections, and natural frequencies. Their great strength is transparency: because every assumption is explicit, engineers can trace exactly why a structure fails and how design changes alter its behavior. They are also computationally cheap, making them suitable for rapid design iterations and code-based verification. The review, however, emphasizes their limitations as well. Real ice accretion is irregular, wind fields are turbulent and spatially varying, and the coupling between towers and lines introduces nonlinearities that simplified hand calculations struggle to capture. When the geometry of ice shedding or the burst of force from a sudden cable release must be modeled in detail, analytical formulas alone run out of explanatory power.

Numerical simulation methods fill that gap. Finite element models can represent a full tower-line system in three dimensions, capturing the nonlinear behavior of cables, the plastic deformation of steel members, and the contact mechanics of ice breaking away from a conductor. The review highlights how such models allow researchers to reproduce catastrophic scenarios in a virtual laboratory, testing how a system responds to combinations of ice thickness, wind speed, and direction that would be dangerous or impossible to stage physically. Detailed analyses of the fundamental assumptions, solution procedures, and uncertainty modeling of these methods form a central part of the paper. Yet numerical simulation carries its own burdens. High-fidelity models demand enormous computational resources, and their predictions are only as good as the inputs they receive: the true shape of the ice, the statistical properties of the wind, and the condition of aging steel all introduce uncertainty that a deterministic model cannot resolve by itself.

This is where stochastic and statistical methods enter the picture. Rather than computing a single deterministic answer, these approaches treat loads, material properties, and structural parameters as random variables and estimate the probability of failure. Wind and ice are inherently stochastic phenomena, and historical records of storms, ice accretion events, and structural damage provide the empirical basis for probabilistic risk assessment. The review examines how these methods quantify uncertainty explicitly, allowing engineers to move beyond the question of whether a tower survives a nominal design load toward the more realistic question of how likely a failure is over the lifetime of the grid. The authors also note the methodological limitations of purely statistical techniques: they depend on the availability and quality of long-term data, and they may struggle to extrapolate to unprecedented storm conditions, precisely the situations that cause the most severe damage.

The fourth family, methods based on artificial intelligence, is the fastest-moving part of the field and a major reason this review is timely. Machine learning models trained on simulation outputs or monitoring data can predict structural responses far faster than a full finite element run, opening the door to near-real-time risk assessment during an unfolding storm. The authors describe AI approaches as showing increasing potential to enhance predictive performance and computational efficiency, a claim that resonates with a broader trend in structural engineering where surrogate models and data-driven classifiers complement physics-based simulation. Still, the review is careful to point out the caveats. AI models can behave as black boxes, their training data may not cover rare extreme events, and their predictions lack the physical interpretability that engineers need to certify safety-critical decisions. The authors treat AI as a powerful complement to mechanics-based understanding, not a replacement for it.

Perhaps the most consequential message of the review is the argument for hybrid strategies. Because each method family illuminates a different facet of the problem, combining them yields assessments that none could deliver alone. An analytical model can provide the physical grounding for a machine learning surrogate; a numerical simulation can generate the training data that a statistical model needs; a probabilistic framework can wrap the whole pipeline in a rigorous treatment of uncertainty. The authors show that this complementarity is not a luxury but a necessity for improving risk assessment, resilience, and future decision-making. In an era when climate change appears to be intensifying both ice storms and extreme wind events in many regions, the cost of relying on any single method is measured in blackouts and collapsed infrastructure.

Beyond cataloging methods, the review identifies key challenges in modeling, computation, and uncertainty quantification that the field has yet to solve. Modeling challenges include representing the complex, time-dependent process of ice accretion and shedding, and capturing the coupled dynamics of long spans with many towers. Computational challenges stem from the sheer scale of full-line simulations, which can involve thousands of degrees of freedom and highly nonlinear behavior over long durations. Uncertainty quantification remains perhaps the deepest difficulty, because the inputs that matter most, such as extreme ice loads and turbulent wind fields, are the hardest to measure and characterize. The authors propose future research directions aimed at intelligent and resilience-oriented strategies, envisioning systems that not only predict failures but support sustainable development of transmission infrastructure under increasingly hostile atmospheric conditions.

For grid operators, regulators, and the public, the stakes of this research are concrete. Power outages triggered by ice-wind hazards cascade into disruptions of heating, hospitals, communications, and water systems, and the economic losses can reach into the billions. The work of Qiu, Liu, and Ban provides a map of where the science stands and where it must go: toward methods that fuse physical insight with data-driven speed, quantify uncertainty honestly, and design grids that bend rather than break. As the discussion of this preprint opens to the research community, the review stands as both a synthesis of decades of effort and a blueprint for the resilient, intelligent power infrastructure the coming decades will demand.

Subject of Research: Dynamic response analysis methods for transmission tower-line systems under combined ice and wind hazards

Article Title: Review article: A review of dynamic response analysis methods for transmission tower-line systems under ice-wind hazards

Article References: Qiu, B., Liu, Y., & Ban, M. (2026). Review article: A review of dynamic response analysis methods for transmission tower-line systems under ice-wind hazards. https://doi.org/10.5194/ms-2026-169

Image Credits: AI Generated

DOI: 10.5194/ms-2026-169

Keywords: transmission towers, ice-wind hazards, dynamic response analysis, structural engineering, finite element simulation, uncertainty quantification, artificial intelligence, power grid resilience, risk assessment, conductor icing, wind loads, Mechanical Sciences

The research, led by Pedro Fernández-Cabán, assistant professor of civil engineering at the FAMU-FSU College of Engineering, together with associate professor Qian Zhang, doctoral student Arezoo Bakhshizadeh and alumnus Peter Tsouroukdissian, set out to answer a question that has long intrigued wind engineers: can macro-scale corrugation of a building envelope meaningfully disrupt the aerodynamic mechanisms that tear roofs off houses and peel cladding from walls? The answer, according to their wind tunnel experiments, is a resounding yes. Models with the deepest wave patterns tested reduced peak wind pressures by 40 to 60 percent near roof and wall corners—the very zones where destructive forces concentrate—across multiple wind directions.

“Changing a building’s shape can significantly reduce the intensity of wind forces it has to withstand,” said Fernández-Cabán. “These nonconventional building shapes reduce the damage from worst-case severe weather scenarios. It’s another tool for engineers and designers to protect against wind damage.” That statement captures a shift in thinking that has been gathering momentum in structural engineering for years. Rather than simply building thicker walls or specifying stronger materials to resist wind loads, engineers can instead reshape the building so that the loads never fully develop in the first place.

To test the concept, the team fabricated 3D-printed scale models of low-rise buildings equipped with wave-shaped exterior roof and wall systems in place of traditional flat surfaces. Three-dimensional printing allowed the researchers to produce precise, repeatable geometries that would have been difficult or impossible to construct by hand. They then systematically varied the depth of the waves, evaluating amplitudes between 5 and 10 percent of the building height, and compared each configuration against a conventional flat-walled control model. Pressure taps embedded in the model surfaces recorded the fluctuating wind pressures at high resolution as the models were subjected to controlled airflow in the college’s wind tunnel.

The physics behind the improvement lies in the behavior of vortices—rotating masses of air that form when wind flows over sharp edges and corners. When wind sweeps smoothly across a flat wall or a pitched roof, the flow separates abruptly at the leading edge, curling back on itself and creating powerful conical vortices that cling to roof corners and wall edges. These vortices generate regions of intense suction, where the local air pressure drops far below the ambient atmospheric pressure. The higher pressure inside the building then pushes outward on the roof or wall surface toward that low-pressure zone, and it is this differential—often acting suddenly and in gusts—that lifts roofing membranes, rips off shingles and tears siding loose. The strongest forces reliably develop at the corners and edges of the roof, where the vortices congregate and pose the greatest threat to structural integrity.

Wave-shaped surfaces attack this mechanism at its root. Instead of presenting a sharp, straight edge where flow can separate cleanly and organize into a coherent vortex, the undulating envelope presents a series of rounded hills and valleys that continuously disrupt the airflow. The wind skips across these contours like a stone bouncing across the surface of a lake, unable to settle into the steady separation patterns that produce concentrated suction loads. Each successive crest and trough breaks up the pressure zones and redirects the flow away from the building envelope, preventing the pockets of high suction from forming in the first place. In effect, the geometry converts one large, coherent, destructive aerodynamic structure into many small, weak, rapidly mixing ones.

The wind tunnel data confirmed this picture quantitatively. Among the configurations tested, the model with the greatest wave depth proved the most effective at alleviating wind load effects, delivering peak pressure reductions of 40 to 60 percent near roof and wall corners across multiple wind directions. That range matters enormously in practice, because hurricanes do not arrive from a single predictable heading, and a mitigation strategy that only works when the wind blows from one quarter would be of limited value. The consistency of the benefit across directions suggests that corrugated envelopes could provide robust, all-around protection rather than a narrow, orientation-dependent advantage.

The economic logic of the approach is equally compelling. Battling wind pressure has long been an ongoing challenge in structural design, and the conventional toolkit reflects that struggle. Exterior architectural features such as rounded corners, sloped walls and stepped setbacks are known to alleviate wind loads, and another common strategy is to make walls thicker or sturdier by adding more or tougher material. These techniques can be effective, but they are expensive. Design and site constraints rule out some features entirely, and retrofitting them onto existing structures can be impractical or prohibitively costly. A corrugated facade, by contrast, modifies the geometry of the envelope itself, potentially adding aerodynamic resilience without demanding dramatic increases in material quantity or fundamentally altering the building’s footprint. The research demonstrates the possibility of adopting building facades with nontraditional shapes as a practical route to wind protection.

The implications of the work extend well beyond the structural engineering community. The underlying fluid dynamics—the behavior of turbulent boundary layers, flow separation and vortex shedding over curved and corrugated surfaces—carry broad relevance for any field that investigates how fluids move around obstacles. “We’re dealing with air, and other engineers and scientists might be dealing with waves and water, but the understanding of fluid dynamics can inform design and engineering across fields,” Fernández-Cabán said. “Aerodynamic optimization requires a multidisciplinary approach that balances structural safety, resilience, material efficiency and performance.” Researchers in aeronautics, environmental science and fundamental physics all grapple with versions of the same problem: how geometry shapes the turbulent flows that determine forces, heat transfer and mixing. Insights from building aerodynamics could inform everything from the design of more efficient aircraft components to models of how wind transports particles and pollutants over rough terrain.

Much work remains before wave-shaped envelopes appear on real construction sites. The current study measured the wind pressures acting on the surfaces of the models, which is the critical first step, but the research team is already conducting additional experiments to better understand the detailed wind flows around these envelope systems—how the air actually moves, separates and reattaches as it travels over the corrugations. The researchers also plan to deploy computational fluid dynamics modeling to further optimize the wave patterns and to explore other surface geometries that were not physically tested in the wind tunnel. Together, these efforts could yield design guidelines that architects and engineers can apply directly, turning an elegant laboratory result into a standard strategy for hurricane resilience. For communities on the front lines of increasingly severe storms, the message from Tallahassee is striking: sometimes the best defense against the wind is not more material, but a better shape.

Subject of Research: Aerodynamic mitigation of hurricane wind loads on low-rise buildings using wave-shaped corrugated wall and roof surfaces

Article Title: FAMU-FSU College of Engineering researchers develop wave-shaped wall and roof designs that protect against hurricane-force winds

Article References: FAMU-FSU College of Engineering researchers develop wave-shaped wall and roof designs that protect against hurricane-force winds. (n.d.). Original publication

Image Credits: AI Generated

DOI: Not provided

Keywords: wind engineering, hurricane resilience, building aerodynamics, wind tunnel testing, vortex dynamics, low-rise buildings, corrugated envelopes, structural engineering, fluid dynamics, wind loads, 3D-printed models, Engineering Structures