740 research outputs found
Supplemental Material - Disadvantaged communities have lower access to urban infrastructure
No full textSupplemental Material for Disadvantaged communities has lower access to urban infrastructure by Leonardo Nicoletti, Mikhail Sirenko and Trivik Verma in Environment and Planning B: Urban Analytics and City Science</p
Supplemental Material - A multi-city study on structural characteristics of bicycle networks
No full textSupplemental Material for A multi-city study on structural characteristics of bicycle networks by Giulia Reggiani, Trivik Verma, Winnie Daamen and Serge Hoogendoorn and Linda Theron in Environment and Planning B: Urban Analytics and City Science</p
Author response: India and China in Africa: a comparative perspective of the oil industry by Raj Verma
No full textEarlier this month Ian Taylor reviewed India and China in Africa, a new book about Asian engagement in the West African oil industry. Here, the book’s author Raj Verma responds to Taylor’s comments, outlining the rationale and evidence for the framework used in the study. India and China in Africa: A comparative perspective of the oil industry. Raj Verma. London: Routledge. 2017
sj-docx-1-usj-10.1177_00420980231207475 – Supplemental material for Cities for citizens! Public value spheres for understanding conflicts in urban planning
No full textSupplemental material, sj-docx-1-usj-10.1177_00420980231207475 for Cities for citizens! Public value spheres for understanding conflicts in urban planning by Rico H Herzog, Juliana E Gonçalves, Geertje Slingerland, Reinout Kleinhans, Holger Prang, Frances Brazier and Trivik Verma in Urban Studies</p
Identification of the Hierarchy in Public Transport Networks based on Passenger Flow Patterns
No full textIn this study, a data-driven, generic and transfer-based methodology for separation and ranking the PTNs has been put forward. With the hierarchy of a network, this is beneficiary for the management and operation of operators for focusing on the higher level network layer and in turn provide better service for passengers. The study introduces three steps to rank the hierarchy of a PTN: (1) using the passenger journey and ride data to derive transfer flow matrix; (2) applying C-space network representation with community detection method to separate and visualize the PTN layer; (3) performing ranking method, regarding inner- and intra- transfer flow. To this end, the hierarchy of a PTN could be presented with temporal attributes. Different day of week and various time period of a day could potentially yield different hierarchy. The proposed unsupervised learning algorithm is based on passenger transfer flow data, independent from geographic location and the mode of transportation. The study shows that the level is changing based on the selected time slot and can be a mixture of different modes, which is dissimilar from the hierarchy purely based on qualitative method
Riverine flood risk screening with a simple network-based approach: A proof of concept in the Ganghes-Brahmaputra basin
No full textFloods cause major problems around the world. Over 35 million people were affected by floods in 2018. They have a growing worldwide impact on life and property. Changes in climate conditions lead to unanticipated variations in glacial runoffs, snowmelt and precipitation, which all significantly changing river flows. An imbalance in river network equilibrium leads to flooding and often ends up causing tremendous damage to society and the environment. Regions that are perceived to be downstream from the source of flooding may end up taking the brunt of the river force due to flood cascades. Floods account for about a third of all natural catastrophes worldwide, they cause more than half of all fatalities and are responsible for a third of the overall economic loss.Modelling approaches are often used to determine flood consequences. Two types of flood models are commonly used: statistical models and flow simulation models. Statistical methods are easy to use but provide limited insight into flood problems. Flow simulation models’ results can be very accurate, especially for hydraulic simulation models. However, these models are expensive to use and develop, and they require a lot of data. These requirements make them unsuitable for application in developing countries and analysing large watersheds. Flood risk screening models try to solve these problems. They are suitable for use in data-sparse regions and are efficient in terms of omputational costs. However, there is a lack of knowledge between river structure and cascading flood effects, and there is a lack of models that are efficient, easy to understand, use topological data and have the purpose of risk screening. In this research, we show a flood model based on complex network theory to efficiently study the cascading effects of floods in riverine systems. Cascading effects are defined as floods that occur as a result of water waves through the system that originate from upstream sources. The developed model uses the hydrological Muskingum routing method. We found that it was possible, notwithstanding many assumptions and a lack of data, to reproduce system behaviour during an extreme flood event in the Ganges-Brahmaputra Basin. Satellite elevation data were used to construct the river network, and satellite precipitation data was used to feed the model. The model can indicate high risk reaches based on the simulated overflow, the flow exceeding a predefined capacity. No existing models are known that can do this, on a laptop, within seven min- utes per simulated day, with limited data for a watershed that exceeds the size of one million square kilometres. The network structure of the model makes it possible to achieve a better understanding between river typology and cascading flood effects. The model is not without its limitations. It cannot pinpoint when and where floods will occur, because it only calculates overflow. Moreover, flood failure mechanisms are not yet included in this model. Failure mechanisms will change model behaviour: when a flood occurs water temporarily leaves the system, which reduces downstream risk. Overflow cascades, therefore, would be shorter in reality than in this model. The model is a proof of concept that shows the potential of a network theory-based risk screening method in flood simulation context. Its properties make it suitable for analysing the effects of changing precipitation patterns, which, for example, could originate from climate change studies. Another use case is real-time forecasting of discharge levels if the mode is combined with real-time discharge levels and precipitations forecasts. The model can be used as an early warning system: alerting when and where high discharge levels are expected. We anticipate our model to be a starting point for policy screening and scenario analysis. Sugges- tions are made to include policy options within the model. Policy analysts can then use the model to compare different policy interventions for all kinds of (future) scenarios. The model should not be seen as a replacement of the advanced hydraulic simulation models, but as a complementary tool useful at an earlier moment in a design process with the purpose of screening options. Ultimately it can become a framework with the aim to support informed decision-making.https://github.com/bcvanmeurs/rnaEngineering and Policy Analysi
Sweeping has no effect on renormalized turbulent viscosity
No full textWe perform renormalization group analysis (RG) of the Navier-Stokes equation in the presence of constant mean velocity field , and show that the renormalized viscosity is unaffected by , thus negating the ``sweeping effect", proposed by Kraichnan [Phys. Fluids {\bf 7}, 1723 (1964)] using random Galilean invariance. Using direct numerical simulation, we show that the correlation functions for and differ from each other, but the renormalized viscosity for the two cases are the same. Our numerical results are consistent with the RG calculations
A Unified Shell model for Buoyancy-Driven Turbulence
No full textWe construct a unified shell model for stably stratified and convective turbulence. Shell model simulation of stably stratified flow in turbulent regime exhibit Bolgiano-Obukhbov (BO) scaling in which the kinetic energy spectrum varies as . However, simulation of convective turbulence shows Kolmogorov's spectrum. These results are consistent with the direct numerical simulations of Kumar {\em et al.} [Phys. Rev. E {\bf 90}, 023016 (2014)]. We also observe a dual scaling ( and ) for a limited range of parameters in stably stratified flow
Energy transfers in small-scale and large-scale dynamos
No full textWe study energy transfers during magnetic energy growth in small-scale and large-scale dynamos. We perform direct numerical simulations for magnetic Prandtl number Pm =20 and 0.2 in a periodic box on 1024^3 grid. Energy fluxes and shell-to-shell energy transfers indicate that in small-scale dynamo for Pm =20, the magnetic energy growth takes place due to a non-local energy transfer from large-scale velocity field to small-scale magnetic field. On the other hand, in large-scale dynamo for Pm =0.2, local energy transfers from large-scale velocity field to large-scale magnetic field takes place
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