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  • 标题:Calibration of HDM-4 Emission Models for Indian Conditions
  • 本地全文:下载
  • 作者:Chandrama Prasad ; Chandrama Prasad ; Aravind Krishna Swamy
  • 期刊名称:Procedia - Social and Behavioral Sciences
  • 印刷版ISSN:1877-0428
  • 出版年度:2013
  • 卷号:104
  • 页码:274-281
  • DOI:10.1016/j.sbspro.2013.11.120
  • 语种:English
  • 出版社:Elsevier
  • 摘要:AbstractThe Highway Development and Management-4 (HDM-4) tool has been widely used for the pavement management activities across the world. This tool has inbuilt pavement performance prediction models, vehicular performance models and economic analysis tools. Exhaust emissions are one of the important outputs of vehicular performance models that are helpful in assessing viability of investment options and environment impact assessment activities. There are seven exhaust emission models (for different components like hydro carbon, carbon monoxide, particulate emissions etc.) available within HDM-4. These models are required to be calibrated so that the predictions made by calibrated HDM-4 models represent the specific local ground conditions. The work presented here is an attempt to calibrate the HDM-4 emission models to Indian conditions. Initially sensitivity analysis of emission models was conducted to find sensitive input variables in emission model that affect model output significantly. It was found that operating weight, pavement gradient and vehicle life are very sensitive inputs into HDM-4 emission models. Based on the sensitivity analysis and data obtained from a previous study were used in calibration of emission models for Indian conditions. Further these calibrated emission models were used to predict emissions for urban conditions prevailing in India. Comparison of predicted and measured values indicate that all emission models for two lane road and Carbon Monoxide emission model for four lane road over-predicts for two wheelers, car, light commercial vehicles and busses, while under-predicting for trucks.
  • 关键词:Highway Development and Management;Calibration;Sensitivity analysis;Emission models
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