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Long-term Trends in Annual Ground Snow Maxima for the Carpathian Region

机译:喀尔巴阡山区年度地面雪最大值的长期趋势

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The current structural design provisions are prevalently based on experience and on the assumption of stationary meteorological conditions. However, the observations of past decades and advanced climate models show that this assumption is debatable. Therefore, this paper examines the historical long-term trends in ground snow load maxima, and their effect on structural reliability. For this purpose, the Carpathian region is selected, and data from a joint research effort of nine countries of the region are used. Annual maxima snow water equivalents are taken, and univariate generalized extreme value distribution is adopted as a probabilistic model. Stationary and five non-stationary distributions are fitted to the observations utilizing the maximum likelihood method. Statistical and information theory based approaches are used to compare the models and to identify trends. Additionally, reliability analyses are performed on a simple structure to explore the practical significance of the trends. The calculations show decreasing trends in annual maxima for most of the region. Although statistically significant changes are detected at many locations, the practical significance - with respect to structural reliability - is considerable only for a few, and the effect is favourable. The results indicate that contrary to the widespread practice in extreme event modelling, the exclusive use of statistical techniques on the analysed extremes is insufficient to identify practically significant trends. This should be demonstrated using practically relevant examples, e.g. reliability of structures.
机译:目前的结构设计规定是基于经验和静止气象条件的假设。然而,过去几十年和高级气候模型的观察表明,这种假设是值得不值得的。因此,本文探讨了地下雪地荷载最大值的历史长期趋势及其对结构可靠性的影响。为此目的,选择喀尔巴阡山脉区域,使用来自该地区九个国家的联合研究努力的数据。采用年度最大雪水等效物,并采用单变量的广义极值分布作为概率模型。静止和五个非静止分布适用于利用最大似然法的观察结果。基于统计和信息理论的方法用于比较模型并识别趋势。此外,可靠性分析是在简单的结构上进行的,以探索趋势的实际意义。该计算显示该地区大部分地区的年度最大值趋势。虽然在许多地方检测到统计学上的显着变化,但是对于结构可靠性的实际意义 - 仅适用于少数几个,效果有利。结果表明,与极端事件建模中的广泛实践相反,分析的极端的独家统计技术不足以识别实际上的趋势。应该使用实际相关的例子来证明这一点,例如,结构的可靠性。

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