# Experimental Study on the Effect of Wind Speed on Hail Impacts
## 1 Introduction  
Hailstorms are highly destructive natural disasters, often accompanied by strong winds and torrential rainfall, causing severe damage to crops and surface-level structures [1, 2, 3, 4]. Data indicate that hailstorms inflict substantial economic losses on transportation systems and building structures worldwide [5, 6]. Furthermore, under the influence of global warming, the annual economic losses attributed to wind-hail disasters are projected to escalate [7, 8]. The impact of hail on building envelopes has garnered significant attention from property owners and stakeholders, presenting unique challenges for both construction materials and agricultural resilience. Despite the high frequency of hail events and their associated damage, the synergistic effects of strong winds on hail impact performance remain poorly understood. Current research predominantly isolates hail impacts from wind interactions, neglecting critical aerodynamic influences such as wind-driven hail acceleration, fragmentation dynamics, and momentum transfer. This knowledge gap underscores the imperative to investigate hail impact behavior under combined wind-hail conditions, which is essential for advancing disaster-resistant design standards and mitigation strategies. [PERSON] et al. [9] conducted a comparative analysis of three simulation methods for modeling hail impacts at medium velocities (10-50 m/s). Their findings demonstrated that the Arbitrary Lagrange-Euler (ALE) method coupled with the MAT155 material model exhibited superior performance in predicting contact force distributions during medium-velocity impacts. [PERSON] et al. [10] developed a strain-rate-sensitive ice material model incorporating scatter-defined compressive strength data for hailstones. This model accurately replicated the failure progression observed in impact experiments, particularly theinitiation and propagation of longitudinal cracks, and elucidated the evolving relationship between these cracks and peak impact forces. [PERSON] et al. [11] employed a hybrid experimental-numerical approach to detect and evaluate the impact characteristics of hailstones with varying diameters on structural components. [PERSON] et al. [12] utilized numerical simulations to investigate the evolution of delamination damage in carbon fiber laminates subjected to repeated hail impacts. Their results revealed that cumulative damage from multiple impacts significantly reduced the load-bearing capacity and increased the likelihood of structural failure. [PERSON] et al. [13] conducted experimental studies on fully bonded single-layer roof system models using a negative-pressure vacuum chamber. Their work established a correlation between hail-induced adhesive failure and the wind resistance degradation of roof systems. [PERSON] et al. [14] quantitatively analyzed the structural response and wind-hail debris penetration resistance of composite structural insulated panels (SIPs) under hail impacts. They further developed fragility curves for SIPs against wind-driven hail impacts using LS-DYNA R7.0 software, providing a predictive framework for a vulnerability assessment. [PERSON] et al. [15] conducted a comparative study on the dynamic responses of membrane structures subjected to hail impacts, incorporating factors such as hailstone diameter, displacement, velocity, and acceleration. Their research combined experimental tests and numerical simulations to evaluate the mechanical behavior of these structures under varying impact conditions. [PERSON] [16] experimentally analyzed the influence of impact location and velocity on the failure mechanisms of composite panels, investigating damage propagation and force transfer during hailstone collisions. The study highlighted how localized stress concentrations and interfacial delamination govern the structural integrity of composite materials under repetitive impacts. [PERSON] [17] developed an experimental methodology to determine the dent resistance of steel roof panels and predict dent depth.