The Mapping Closure Approximation(MCA)approach is developed to describe the statistics of both conserved and reactive scalars in random flows.The statistics include Probability Density Function(PDF),Conditional Dissip...The Mapping Closure Approximation(MCA)approach is developed to describe the statistics of both conserved and reactive scalars in random flows.The statistics include Probability Density Function(PDF),Conditional Dissipation Rate(CDR)and Conditional Laplacian(CL).The statistical quantities are calculated using the MCA and compared with the results of the Direct Nu- merical Simulation(DNS).The results obtained from the MCA are in agreement with those from the DNS.It is shown that the MCA approach can predict the statistics of reactive scalars in random flows.展开更多
基金The project supported by the National Committee of Science and Technology,China,under the Special Funds for Major Basic Research Project (G2000077305 and G1999032801),and the National Natural Science Foundation of China (10325211)
文摘The Mapping Closure Approximation(MCA)approach is developed to describe the statistics of both conserved and reactive scalars in random flows.The statistics include Probability Density Function(PDF),Conditional Dissipation Rate(CDR)and Conditional Laplacian(CL).The statistical quantities are calculated using the MCA and compared with the results of the Direct Nu- merical Simulation(DNS).The results obtained from the MCA are in agreement with those from the DNS.It is shown that the MCA approach can predict the statistics of reactive scalars in random flows.
