activity
20192022
most citedArrhenius.jl: A Differentiable Combustion SimulationPackage

5 citations · 7 across the 4 of their papers we have counts for

collaborators

6 papers

physics.chem-ph20222 cited

Kinetics Parameter Optimization via Neural Ordinary Differential Equations

Xingyu Su, Weiqi Ji, Jian An +3

Chemical kinetics mechanisms are essential for understanding, analyzing, and simulating complex combustion phenomena. In this study, a Neural Ordinary Differential Equation (Neural…

physics.flu-dyn2021

Neural Differential Equations for Inverse Modeling in Model Combustors

Xingyu Su, Weiqi Ji, Long Zhang +3

Monitoring the dynamics processes in combustors is crucial for safe and efficient operations. However, in practice, only limited data can be obtained due to limitations in the meas…

physics.chem-ph20215 cited

Arrhenius.jl: A Differentiable Combustion SimulationPackage

Weiqi Ji, Xingyu Su, Bin Pang +6

Combustion kinetic modeling is an integral part of combustion simulation, and extensive studies have been devoted to developing both high fidelity and computationally affordable mo…

physics.flu-dyn2021

Large eddy simulation of a supersonic lifted hydrogen flame with sparse-Lagrangian multiple mapping conditioning approach

Zhiwei Huang, Matthew J. Cleary, Zhuyin Ren +1

The Multiple Mapping Conditioning / Large Eddy Simulation (MMC-LES) approach is used to simulate a supersonic lifted hydrogen jet flame, which features shock-induced autoignition,…

physics.flu-dyn2020

Kinetic Similarity between Extinction Strain Rate and Laminar Flame Speed

Weiqi Ji, Tianwei Yang, Zhuyin Ren +1

Extinction strain rate (ESR) and laminar flame speed (LFS) are fundamental properties of a fuel/air mixture that are often utilized as scaling parameters in turbulent combustion. W…

stat.ML2019

Uncertainty Propagation in Deep Neural Network Using Active Subspace

Weiqi Ji, Zhuyin Ren, Chung K. Law

The inputs of deep neural network (DNN) from real-world data usually come with uncertainties. Yet, it is challenging to propagate the uncertainty in the input features to the DNN p…