Ground-motion selection is essential as an input for dynamic structural analyses. Although recent studies have highlighted the importance of target variance as auxiliary criteria and introduced selection methods, they typically require a trade-off between computational expense and accuracy. This paper presents an efficient and accurate method for ground-motion selection and scaling that matches both the target mean and standard deviation, while using either a single-objective- or multi-objective-based pattern-search optimization technique. The selection algorithm was tested using the code-based and conditional-spectrum-based target spectrum for various design scenarios. The results indicated that the pattern-search-based selection algorithm is an optimal method as it provides the best-matching records suite with a more precise and quicker selection than other notable optimization techniques.

地面运动选择作为动态结构分析的输入是必不可少的。尽管最近的研究强调了目标方差作为辅助标准的重要性并引入了选择方法，但它们通常需要在计算成本和准确性之间进行权衡。本文提出了一种有效且准确的地面运动选择和缩放方法，该方法匹配目标均值和标准偏差，同时使用基于单目标或多目标的模式搜索优化技术。针对各种设计场景，使用基于代码和基于条件频谱的目标频谱对选择算法进行了测试。