Mechanical Analog for Cities
Nicos Makris, Gholamreza Moghimi, Eric Godat, and Tue Vu

TL;DR
This paper develops a mechanical analog model for cities using concepts from statistical mechanics, enabling prediction of urban responses to hazards and demonstrating resilience through GPS data analysis.
Contribution
It introduces a novel approach applying mechanical analogs to model city dynamics and responses to hazards based on GPS data and microrheology concepts.
Findings
Mechanical analogs predict city response to hazards accurately.
Cities show inherent resilience, reverting quickly after shocks.
Model aligns well with real GPS data from Dallas storm.
Abstract
Motivated from the increasing need to develop a quantitative, science-based, predictive understanding of the dynamics and response of cities when subjected to hazards, in this paper we apply concepts from statistical mechanics and microrheology to develop mechanical analogs for cities with predictive capabilities. We envision a city to be a matrix where people (cell-phone users) are driven by the economy of the city and other associated incentives while using the collection of its infrastructure networks in a similar way that thermally driven Brownian probe particles are moving within a complex viscoelastic material. Mean-square displacements (ensemble averages) 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…
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Taxonomy
TopicsUrban Design and Spatial Analysis · Tree Root and Stability Studies · Landslides and related hazards
