Koenig, Benjamin C., and Deng, Sili. Multi-target active subspaces generated using a neural network for computationally efficient turbulent combustion kinetic uncertainty quantification in the flamelet regime. Retrieved from https://par.nsf.gov/biblio/10498250. Combustion and Flame 258.P2 Web. doi:10.1016/j.combustflame.2023.113015.

Koenig, Benjamin C., & Deng, Sili. Multi-target active subspaces generated using a neural network for computationally efficient turbulent combustion kinetic uncertainty quantification in the flamelet regime. Combustion and Flame, 258 (P2). Retrieved from https://par.nsf.gov/biblio/10498250. https://doi.org/10.1016/j.combustflame.2023.113015

Koenig, Benjamin C., and Deng, Sili. "Multi-target active subspaces generated using a neural network for computationally efficient turbulent combustion kinetic uncertainty quantification in the flamelet regime". Combustion and Flame 258 (P2). Country unknown/Code not available: Elsevier. https://doi.org/10.1016/j.combustflame.2023.113015. https://par.nsf.gov/biblio/10498250.

@article{osti_10498250,
place = {Country unknown/Code not available}, title = {Multi-target active subspaces generated using a neural network for computationally efficient turbulent combustion kinetic uncertainty quantification in the flamelet regime}, url = {https://par.nsf.gov/biblio/10498250}, DOI = {10.1016/j.combustflame.2023.113015}, abstractNote = {}, journal = {Combustion and Flame}, volume = {258}, number = {P2}, publisher = {Elsevier}, author = {Koenig, Benjamin C. and Deng, Sili}, }