PCAfold 2.0—Novel tools and algorithms for low-dimensional manifold assessment and optimization

Zdybał, Kamila; Armstrong, E. F.; Parente, Alessandro; Sutherland, James C.

doi:10.1016/j.softx.2023.101447

Cited by 5 publications

(3 citation statements)

References 8 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…While clustering techniques are not within the scope of this study, we use the clustering approach implemented in the PCAfold 2.0 software [36]. This software implements a zero-neighborhood clustering technique, which clusters data by separating close-to-zero observations into one or two clusters.…”

Section: Data Clusteringmentioning

confidence: 99%

See 1 more Smart Citation

A Data-Based Hybrid Chemistry Acceleration Framework for the Low-Temperature Oxidation of Complex Fuels

Alqahtani,

Gitushi,

Echekki

2024

Energies

View full text Add to dashboard Cite

The oxidation of complex hydrocarbons is a computationally expensive process involving detailed mechanisms with hundreds of chemical species and thousands of reactions. For low-temperature oxidation, an accurate account of the fuel-specific species is required to correctly describe the pyrolysis stage of oxidation. In this study, we develop a hybrid chemistry framework to model and accelerate the low-temperature oxidation of complex hydrocarbon fuels. The framework is based on a selection of representative species that capture the different stages of ignition, heat release, and final products. These species are selected using a two-step principal component analysis of the reaction rates of simulation data. Artificial neural networks (ANNs) are used to model the source terms of the representative species during the pyrolysis stage up to the transition time. This ANN-based model is coupled with C0–C4 foundational chemistry, which is used to model the remaining species up to the transition time and all species beyond the transition time. Coupled with the USC II mechanism as foundational chemistry, this framework is demonstrated using simple reactor homogeneous chemistry and perfectly stirred reactor (PSR) calculations for n-heptane oxidation over a range of composition and thermodynamic conditions. The hybrid chemistry framework accurately captures correct physical behavior and reproduces the results obtained using detailed chemistry at a fraction of the computational cost.

show abstract

Section: Data Clusteringmentioning

confidence: 99%

“…The offset percentage from zero at which splits are performed is set to 2.5 and 1 for the first and second stages of ignition, respectively. The clustering is performed as follows [36]:…”

Section: Data Clusteringmentioning

confidence: 99%

A Data-Based Hybrid Chemistry Acceleration Framework for the Low-Temperature Oxidation of Complex Fuels

Alqahtani,

Gitushi,

Echekki

2024

Energies

View full text Add to dashboard Cite

show abstract

“… 69 To enable researchers to apply the QoI-aware encoder-decoder approach to their own datasets, we have implemented all of the relevant functionalities in our open-source Python library, PCAfold . 70 , 71 The user can easily implement the QoI-aware encoder-decoder by instantiating an object of the QoIAwareProjection class from the utilities module. The PCAfold library is required to reproduce our results.…”

Section: Data and Code Availabilitymentioning

confidence: 99%