Probability Density Function Modeling

Probability Density Function Modeling is a computational method in turbulent combustion that belongs to the class of statistical modeling techniques, specifically characterized by its use of a probability density function to describe the random fluctuations of thermochemical variables in turbulent reactive flows.

2.8K

Publications

138.1K

Citations

6.6K

Authors

2K

Institutions

Publications per year

2017–2026

531

Variants

Pdf Modeling

Authors

6.6K

  1. SB
    Stephen B. Pope

    Cornell University, United States

    52 publications · 6.4K citations

    36

    h-index

  2. GM
    Gauss M. Cordeiro

    Universidade Federal de Pernambuco, Brazil

    33 publications · 1.6K citations

    22

    h-index

  3. MA
    Mohamed‐Slim Alouini

    King Abdullah University of Science and Technology, Saudi Arabia

    16 publications · 920 citations

    13

    h-index

  4. RO
    Rodney O. Fox

    Iowa State University, United States

    12 publications · 550 citations

    12

    h-index

  5. EM
    Edwin M. M. Ortega

    Universidade de São Paulo, Brazil

    13 publications · 559 citations

    11

    h-index

1–5 of 6.6K

Venues

  1. Combustion and Flame

    50 publications · 3.1K citations

    33

    h-index

  2. IEEE Transactions on Vehicular Technology

    39 publications · 2.7K citations

    27

    h-index

  3. Physics of Fluids

    41 publications · 1.9K citations

    26

    h-index

  4. IEEE Transactions on Communications

    39 publications · 2.1K citations

    25

    h-index

  5. IEEE Transactions on Signal Processing

    39 publications · 2.5K citations

    25

    h-index

1–5