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城市的机械模拟物。

Mechanical analogue for cities.

作者信息

Makris Nicos, Moghimi Gholamreza, Godat Eric, Vu Tue

机构信息

Department of Civil and Environmental Engineering, OIT, Southern Methodist University, Dallas, TX 75276, USA.

Data Science and Research Services, OIT, Southern Methodist University, Dallas, TX 75276, USA.

出版信息

R Soc Open Sci. 2023 Mar 8;10(3):220943. doi: 10.1098/rsos.220943. eCollection 2023 Mar.

Abstract

Motivated from the increasing need to develop a science-based, predictive understanding of the dynamics and response of cities when subjected to natural hazards, in this paper, we apply concepts from statistical mechanics and microrheology to develop mechanical analogues for cities with predictive capabilities. We envision a city to be a matrix where cell-phone users are driven by the city's economy and other incentives while using the collection of its infrastructure networks in a similar way that thermally driven Brownian particles are moving within a complex viscoelastic material. Mean-square displacements of thousands of cell-phone users are computed from GPS location data to establish the creep compliance and the resulting impulse response function of a city. The derivation of these time-response functions allows the synthesis of simple mechanical analogues that model satisfactorily the city's behaviour under normal conditions. Our study concentrates on predicting the response of cities to acute shocks (natural hazards) that are approximated with a rectangular pulse; and we show that the derived solid-like mechanical networks predict that cities revert immediately to their pre-event response suggesting an inherent resilience. Our findings are in remarkable good agreement with the recorded response of the Dallas metroplex following the February 2021 North American winter storm.

摘要

鉴于对基于科学、预测性地理解城市在遭受自然灾害时的动态和响应的需求不断增加,本文运用统计力学和微观流变学的概念,开发具有预测能力的城市力学模拟模型。我们设想城市是一个矩阵,其中手机用户受城市经济和其他激励因素驱动,同时以类似于热驱动的布朗粒子在复杂粘弹性材料中移动的方式使用城市的基础设施网络集合。通过GPS位置数据计算数千名手机用户的均方位移,以建立城市的蠕变柔量和由此产生的脉冲响应函数。这些时间响应函数的推导使得能够合成简单的力学模拟模型,该模型能令人满意地模拟城市在正常条件下的行为。我们的研究专注于预测城市对以矩形脉冲近似的急性冲击(自然灾害)的响应;并且我们表明,推导得出的类固体力学网络预测城市会立即恢复到事件前的响应,这表明城市具有内在的恢复力。我们的研究结果与2021年2月北美冬季风暴后达拉斯都会区的记录响应非常吻合。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3058/9993048/05d99a0c7bdf/rsos220943f01.jpg

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