Nonlinear seismic analysis is becoming increasingly significant to grasp the performance of structures under earthquake. A nonlinear finite element model of existing bridge at Karad, India, including the bridge structure, pile groups, and the supporting foundation soil, is developed under 2D and 3D conditions in Gid (a pre and postprocessor software). The computational model is analyzed using Parallel OpenSees. OpenSees is open source software for carrying out earthquake engineering simulations, developed by Pacific Earthquake Engineering Research Centre, USA. The earthquake simulations were carried out using C-DAC's high performance computing facilities. The ground motion selection and modification technique-predicting median interstory drift response of building, ground motions are selected by M and R and scaling to Sa(T1), is used for seismic response of combined large scale soil-structure interaction of Karad bridge. The idealized model properly represents the actual geometry; boundary conditions, gravity loads and mass distribution. Nonlinear modeling and analysis allows more accurate determination of stresses, strains, deformations and forces of critical components. The present work involves the effects of specially varying input excitation (earthquakes) at an existing bridge site. A nonlinear finite element model of this bridge site including the bridge structure, pile group and supporting foundation soil is developed in 2D plane strain conditions and in 3D 20 noded brick element. Carefully calibrated nonlinear stress-strain models are employed for both bridge and soil materials, in order to realistically reproduce actual site conditions. Seismic input motions are defined as forces using the boundary layer force method (zero length element approach). The earthquake simulation of bridge structure includes large scale interaction between structure-foundation-soil system and deformations at various locations of the bridge. The results include deformations at base of piers and at various spans of the bridge. Performing the bridge simulation on C-DAC's Param Yuva facility results in accuracy and saving in computing efforts.
Global urban population is projected to double by 2050. This rapid urbanization is the driver of economic growth but has environmental challenges. To that end, there is an urgent need to understand, simulate and disseminate information about extreme events, routine city operations and long term planning decisions.This paper describes an effort underway in India involving an interdisciplinary community of meteorology, hydrology, air quality, computer science from national and international institutes. The urban Collaboratory is a system of systems for simulating weather, hydrology, air quality, health, energy, transport and economy, and its interactions. Study and prediction of urban events involve multi-scale observations and cross-sector models; heterogeneous data management and enormous computing power. The consortia program (NSM_Urban) is part of ‘weather ready cities’, under the aegis of India’s National Supercomputing Mission.The ecosystem ‘Urban Environment Science to Society (UES2S)’, builds on the integrated cyberinfrastructure with a science gateway for community research and end-user service with modeling and inter-operable data. The Collaboratory has urban computing, stakeholder participation, and a coordinated means to scaffold projects and ideas into operational tools. It discusses the design and the utilization of the High Performance Computing (HPC) as a science cloud platform for bridging urban environment and data science, participatory stakeholder applications and decision making. The system currently integrates models for high impact urban weather, flooding, air quality, and simulating street and building scale wind flow and dispersion. The program with the work underway is ripe for interfacing with regional and international partners and this paper provides an avenue towards that end.
<p>Meteorology and Hydrological extreme events, such as heavy rainfall and associated Flooding is one of the increasing disasters in India for last two decades. Due to heavy reservoir discharge, Impact of rapid Urbanization, unauthorized encroachments across riverbanks extreme flood events are likely to be more common and severe in the future, potentially impacting millions of people.</p> <p>Pune one the fastest growing megacities in India facing frequent riverine flooding and associated disaster causing huge property losses in millions and causalities. The city is located at the leeward side of Sahyadri mountain range, with 7 reservoirs on the upstream side of the catchment, which control the flows in the rivers impacting the downstream Urban catchment. The reservoirs spillway discharges causes riverine flooding along with contribution from free catchment runoff, which usually occur concurrently. Estimation of reservoir inflows and subsequent spillway discharges is needed for integrated reservoir operations to execute effective flood control measures. To understand these severe flood disasters associated with reservoir operation ensemble multi model simulations were carried for Pune catchment for flood mitigation.</p> <p>In current study, coupled meteorology model WRF with integrated high resolution (10m) hydrology model HEC-HMS and Hydraulic Model HEC-RAS was developed. High resolution CartoSAT, Digital Elevation Model (DEM) and generated 1m DTM was used to develop both hydraulic and hydrology models. The geometric data for dam structures and gates/spillways have been incorporated in developed models. Gates were operated based on reservoir rule curves for spillway discharge and riverine flood simulations. Spatially distributed high-resolution WRF (1.5 Km) forecasted (72 Hrs.) gridded rainfall data with temporal resolution of 15 mins has been used for forecasting the flood condition in the city. 3D buildings have been incorporated in the terrain to recognize water depth and flooding in the city, which can be visualized through 2-dimensional Rasmapper and 3-dimensional viewer.&#160; The performance of the models has been validated on the basis of statistical error functions (NSE, RSR, PBIAS and R<sup>2</sup>). Pune flood disaster events for the year 2019 and 2022 were simulated by developed flood forecasting system with reservoir operations. The model output (water level, spread and discharge) were validated using observed flood data from Pune Municipal corporation and dam discharges from water Resource department.</p> <p>The developed multi-model flood forecasting framework will help the reservoir authorities to perform reservoir operations effectively in future to minimize the downstream flood conditions. Also the disaster management authorities will plan flood mitigation plans with sufficient lead time.</p>
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