考虑脉动风的随机性，采用可靠度理论计算不同平均风速下列车曲线通过的失效概率，分析内外侧横风下列车的运行安全性，建立不同失效概率下列车的风速-车速运行安全域。首先，采用风速功率谱密度函数，利用谐波叠加法对列车受到的非定常气动载荷进行模拟，选取中国高速铁路无砟轨道谱作为轨道不平顺激励；其次，采用SIMPACK建立列车的多体系统动力学模型，将气动载荷与轨道不平顺作为外部激励，计算不同平均风速下列车以不同车速过曲线时的安全性评价指标，得到轮重减载率对车速和风速的变化最敏感；最后，基于可靠度理论使用轮重减载率构造功能函数，并采用支持向量机回归的代理模型拟合极限状态方程，计算不同风速和车速下列车运行的失效概率，得到不同概率下列车的内外侧风安全域，并与传统确定性方法得到的列车曲线通过安全域进行比较。结果表明：车速不变时，较大的失效概率具有更大的风速安全域；随着车速的提高外侧横风下列车安全风速先升高后降低，而内侧横风下列车安全风速随车速的升高一直降低；车速较小时外侧风具有比内侧风更低的安全风速，车速较大时内侧风具有比外侧风更低的安全风速；与传统确定性方法得到的列车曲线通过安全域相比，采用可靠度方法计算的列车概率特征风曲线能更好地体现安全风速随车速的变化规律。

Considering the randomness of fluctuating wind, reliability theory was applied to calculate the failure probability of a train passing through a curve under different mean wind speeds. The operational safety of the train under crosswinds from both the inner and outer sides was analyzed, and the wind speed-train speed operational safety domain under different failure probabilities was established. Firstly, the unsteady aerodynamic load on the train was simulated by using the harmonic superposition method with the wind speed power spectral density function. The Chinese high-speed railway ballastless track spectrum was selected as the track irregularity excitation. Secondly, a multi-body system dynamics model of the train was established using SIMPACK. The aerodynamic load and track irregularity were applied as external excitations. The safety evaluation indicators of the train passing through the curve at different speeds under different mean wind speeds were calculated. The wheel load reduction rate was found to be the most sensitive to changes in speed and wind speed. Finally, based on reliability theory, the wheel load reduction rate was used to construct a performance function. A surrogate model based on support vector machine regression was employed to fit the limit state equation. The failure probability of train operation under different wind speeds and train speeds was calculated. The inner and outer wind safety domains of the train under different probabilities were obtained and compared with the train curve-passing safety domain derived from traditional deterministic methods. The results indicate that when the train speed remains constant, a larger failure probability corresponds to a larger wind speed safety domain. Under external crosswinds, the safe wind speed first increases and then decreases as the train speed increases, while under internal crosswinds, the safe wind speed consistently decreases with increasing train speed. At lower train speeds, external crosswinds result in lower safe wind speeds compared to internal crosswinds, whereas at higher train speeds, internal crosswinds lead to lower safe wind speeds than external crosswinds. Compared to the safety domain obtained using traditional deterministic methods for train curves, the probabilistic characteristic wind curve calculated using reliability methods for trains better reflects the variation of safe wind speeds with train speed.