[{"data":1,"prerenderedAt":52},["ShallowReactive",2],{"research-hkust-researchers-break-the-mapping-bottleneck-in-inflow-turbulence-generation-for-atmospheric-boundary-layer-simulations-with-adaptive-energy-preserving-mapping-strategy":3},{"id":4,"title":5,"body":6,"cover":37,"date":38,"description":12,"extension":39,"link":40,"meta":41,"navigation":42,"path":43,"researchId":44,"seo":45,"slug":46,"source":47,"stem":48,"tags":49,"__hash__":51},"research\u002Fresearch\u002F33-hkust-researchers-break-the-mapping-bottleneck-in-inflow-turbulence-generation-for-atmospheric-boundary-layer-simulations-with-adaptive-energy-preserving-mapping-strategy.md","HKUST Researchers Break the \"Mapping Bottleneck\" in Inflow Turbulence Generation for Atmospheric Boundary Layer Simulations with Adaptive Energy-Preserving Mapping Strategy",{"type":7,"value":8,"toc":33},"minimark",[9,13,26],[10,11,12],"p",{},"This work focuses on developing a reliable inflow turbulence generation method for the numerical simulations of atmospheric boundary layers (ABLs), which is crucial for predicting extreme weather disasters, heat-island effect, and pollutant dispersion in the urban areas. Existing inflow turbulence generation methods suffer from unrealistic vertical spatial correlation properties when mapping homogeneous turbulence fields onto realistic ABLs. To address this, an adaptive energy-preserving mapping (AEPM) algorithm for synthesizing inflow turbulence in large-eddy simulations (LESs) is proposed. The AEPM maps the RFG-generated inflow turbulence with the spatial weighting functions described by the Gaussian functions. Adaptive shape- and scale-correcting algorithms are proposed to match the target turbulent kinetic energy, spatial correlation, and flow continuity of the ABLs. The AEPM is comprehensively validated through three sets of LESs, including the ABLs around a rectangular building under neutral and unstable thermal stratifications and that over flat terrain. The simulation results match well with the wind-tunnel experimental results in the time-averaged distributions of streamwise velocity, pollutant distribution, and temperature in all the tested cases. The wall-modeled LES (WMLES) exhibits comparable accuracy to the wall-resolved LES (WRLES), but with much reduced computational costs. The AEPM shows great potential in supporting accurate predictions of airflow, pollutant dispersion, and heat transfer in urban environments.",[14,15,16,17,16,22],"figure",{},"\n  ",[18,19],"img",{"src":20,"style":21},"https:\u002F\u002Fmedia.meteonex.hkust.edu.hk\u002Fportals\u002FCCRS\u002Fpublic\u002Fimages\u002Fresearch\u002FAEPM.png","width: 70%",[23,24,25],"figcaption",{},"\n  Time-averaged (a–c) and instantaneous (d–f) values of the AEPM-generated numerical results for velocity (a, d), pollutant concentration (b, e), and temperature (c, f) around a building.\n  ",[10,27,28,32],{},[29,30,31],"em",{},"Authors:"," Shiyi Lu, Anjia Ying, Mengqian Lu(Director of CCRS), Lin Fu(Member of CCRS)*",{"title":34,"searchDepth":35,"depth":35,"links":36},"",2,[],"https:\u002F\u002Fmedia.meteonex.hkust.edu.hk\u002Fportals\u002FCCRS\u002Fpublic\u002Fimages\u002Fresearch\u002Fcover\u002Fid33.png","2026-08-14","md",null,{},true,"\u002Fresearch\u002F33-hkust-researchers-break-the-mapping-bottleneck-in-inflow-turbulence-generation-for-atmospheric-boundary-layer-simulations-with-adaptive-energy-preserving-mapping-strategy",33,{"title":5,"description":12},"hkust-researchers-break-the-mapping-bottleneck-in-inflow-turbulence-generation-for-atmospheric-boundary-layer-simulations-with-adaptive-energy-preserving-mapping-strategy","local","research\u002F33-hkust-researchers-break-the-mapping-bottleneck-in-inflow-turbulence-generation-for-atmospheric-boundary-layer-simulations-with-adaptive-energy-preserving-mapping-strategy",[50],"climate","TOW0JnOO_meZUQYadXMeKWOuHFHep6DA3IBewq3i7G0",1792997703042]