The optimization and machine learning toolkit (OMLT) is an open-source software package
incorporating neural network and gradient-boosted tree surrogate models, which have been …

In order to achieve net-zero emissions until 2050, it is of utmost importance to improve the
energy efficiency and thereby reduce the greenhouse gas emissions in the chemical …

Highlights•Systematically review 82 model-based design (MBD) toolkits.•Dynamic,
multiscale, and interdisciplinary grand challenges drive software trends.•Organize MBD …

Future electricity generation systems must be optimized to provide flexibility that counteracts
the variability of non-dispatchable renewable energy sources and ensures the reliability and …

Low-salt-rejection reverse osmosis (LSRRO) is an emerging membrane-based desalination
technology for concentrating brines with potentially lower energy consumption and cost than …

Abstract Machine learning models are promising as surrogates in optimization when
replacing difficult to solve equations or black-box type models. This work demonstrates the …

Current legislation calling for the phase out of hydrofluorocarbon (HFC) refrigerants is
driving a global market shift that has prompted industry and research institutions to …

Accelerating the deep decarbonization of the world's electric grids requires the coordination
of complex energy systems and infrastructures across timescales from seconds to decades …

Predictive mathematical models are a cornerstone of science and engineering. Yet
selecting, calibrating, and validating said science‐based models often remains an art in …

There is increasing interest in utility-scale solar power plants with storage which can flexibly
dispatch renewable energy to the grid. However, plant design possesses many degrees of …