Machine learning-enabled techno-economic uncertainty analysis of sustainable aviation fuel production pathways

Wu, Chao; Wang, Yuxi; Tao, Ling

doi:10.1016/j.ceja.2024.100650

Title: Machine learning-enabled techno-economic uncertainty analysis of sustainable aviation fuel production pathways

Journal Article · 31 October 2024 · Chemical Engineering Journal Advances

DOI: https://doi.org/10.1016/j.ceja.2024.100650 · OSTI ID:2455043

Wu, Chao; Wang, Yuxi;

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Research Organization:: National Renewable Energy Laboratory (NREL), Golden, CO (United States)

Sponsoring Organization:: USDOE Office of Energy Efficiency and Renewable Energy (EERE), Office of Sustainable Transportation. Bioenergy Technologies Office (BETO)

Grant/Contract Number:: AC36-08GO28308

OSTI ID:: 2455043

Report Number(s):: NREL/JA--5100-87810; S266682112400067X; 100650; PII: S266682112400067X

Journal Information:: Chemical Engineering Journal Advances, Journal Name: Chemical Engineering Journal Advances Journal Issue: C Vol. 20; ISSN 2666-8211

Publisher:: ElsevierCopyright Statement

Country of Publication:: Netherlands

Language:: English

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97 MATHEMATICS AND COMPUTING
Monte Carlo method
machine learning
minimum fuel selling price (MFSP)
techno-economic analysis (TEA)
uncertainty analysis

Title: Machine learning-enabled techno-economic uncertainty analysis of sustainable aviation fuel production pathways

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