The sensitivity of Doppler wind lidar is an important parameter which affects the performance of Doppler wind lidar. Aerosol scattering ratio, atmospheric temperature, and wind speed obviously affect the measurement o...The sensitivity of Doppler wind lidar is an important parameter which affects the performance of Doppler wind lidar. Aerosol scattering ratio, atmospheric temperature, and wind speed obviously affect the measurement of Doppler wind lidar with iodine filter. We discuss about the relationship between the measurement sensitivity and the above atmospheric parameters. The numerical relationship between them is given through the theoretical simulation and calculation.展开更多
Since AASHTO released the Mechanistic-Empirical Pavement Design Guide （MEPDG） for public review in 2004, many highway research agencies have performed sensitivity ana- lyses using the prototype MEPDG design software...Since AASHTO released the Mechanistic-Empirical Pavement Design Guide （MEPDG） for public review in 2004, many highway research agencies have performed sensitivity ana- lyses using the prototype MEPDG design software. The information provided by the sensitivity analysis is essential for design engineers to better understand the MEPDG design models and to identify important input parameters for pavement design. In literature, different studies have been carried out based on either local or global sensitivity analysis methods, and sensitivity indices have been proposed for ranking the importance of the input parameters. In this paper, a regional sensitivity analysis method, Monte Carlo filtering （MCF）, is presented. The MCF method maintains many advantages of the global sensitivity analysis, while focusing on the regional sensitivity of the MEPDG model near the design criteria rather than the entire problem domain. It is shown that the information obtained from the MCF method is more helpful and accurate in guiding design engineers in pavement design practices. To demonstrate the proposed regional sensitivity method, a typical three-layer flexible pavement structure was analyzed at input level 3. A detailed procedure to generate Monte Carlo runs using the AASHTOWare Pavement ME Design software was provided. The results in the example show that the sensitivity ranking of the input parameters in this study reasonably matches with that in a previous study under a global sensitivity analysis. Based on the analysis results, the strengths, practical issues, and applications of the MCF method were further discussed,展开更多
基金the National Natural Science Foundation of China under Grant No.40427001,60578038,and 40505003
文摘The sensitivity of Doppler wind lidar is an important parameter which affects the performance of Doppler wind lidar. Aerosol scattering ratio, atmospheric temperature, and wind speed obviously affect the measurement of Doppler wind lidar with iodine filter. We discuss about the relationship between the measurement sensitivity and the above atmospheric parameters. The numerical relationship between them is given through the theoretical simulation and calculation.
基金sponsored by the Louisiana Transportation Research Centerthe Louisiana Department of Transportation and Development
文摘Since AASHTO released the Mechanistic-Empirical Pavement Design Guide （MEPDG） for public review in 2004, many highway research agencies have performed sensitivity ana- lyses using the prototype MEPDG design software. The information provided by the sensitivity analysis is essential for design engineers to better understand the MEPDG design models and to identify important input parameters for pavement design. In literature, different studies have been carried out based on either local or global sensitivity analysis methods, and sensitivity indices have been proposed for ranking the importance of the input parameters. In this paper, a regional sensitivity analysis method, Monte Carlo filtering （MCF）, is presented. The MCF method maintains many advantages of the global sensitivity analysis, while focusing on the regional sensitivity of the MEPDG model near the design criteria rather than the entire problem domain. It is shown that the information obtained from the MCF method is more helpful and accurate in guiding design engineers in pavement design practices. To demonstrate the proposed regional sensitivity method, a typical three-layer flexible pavement structure was analyzed at input level 3. A detailed procedure to generate Monte Carlo runs using the AASHTOWare Pavement ME Design software was provided. The results in the example show that the sensitivity ranking of the input parameters in this study reasonably matches with that in a previous study under a global sensitivity analysis. Based on the analysis results, the strengths, practical issues, and applications of the MCF method were further discussed,
