Publications of Lihong Feng

Zhang, Y.; Feng, L.; Seidel-Morgenstern, A.; Benner, P.: Accelerating Optimization and Uncertainty Quantification of Nonlinear SMB Chromatography Using Reduced-Order Models. Computers & Chemical Engineering 96, pp. 237 - 247 (2017)

Feng, L.; Yue, Y.; Banagaaya, N.; Meuris, P.; Schoenmaker, W.; Benner, P.: Parametric Modeling and Model Order Reduction for (Electro-)Thermal Analysis of Nanoelectronic Structures. Journal of Mathematics in Industry 6 (1), 10, 16 pages (2016)

ter Maten, E. J. W.; Putek, P.; Günther, M.; Pulch, R.; Tischendorf, C.; Strohm, C.; Schoenmaker, W.; Meuris, P.; de Smedt, B.; Benner, P. et al.; Feng, L.; Banagaaya, N.; Yue, Y.; Janssen, R.; Dohmen, J. J.; Tasić, B.; Deleu, F.; Gillon, R.; Wieers, A.; Brachtendorf, H.-G.; Bittner, K.; Kratochvíl, T.; Petřzela, J.; Sotner, R.; Göthans, T.; Dřínovský, J.; Schöps, S.; Duque Guerra, D. J.; Casper, T.; De Gersem, H.; Römer, U.; Reynier, P.; Barroul, P.; Masliah, D.; Rousseau, B.: Nanoelectronic COupled Problems Solutions - nanoCOPS: Modelling, Multirate, Model Order Reduction, Uncertainty Quantification, Fast Fault Simulation. Journal of Mathematics in Industry 7 (1), 2, 19 pages (2016)

Ahuja, K.; Benner, P.; de Sturler, E.; Feng, L.: Recycling BiCGSTAB with an Application to Parametric Model Order Reduction. SIAM Journal on Scientific Computing 37 (5), pp. S429 - S446 (2015)

Zhang, Y.; Feng, L.; Li, S.; Benner, P.: An Efficient Output Error Estimation for Model Order Reduction of Parametrized Evolution Equations. SIAM Journal on Scientific Computing 37 (6), pp. B910 - B936 (2015)

Chellappa, S.; Feng, L.; Benner, P.: An Adaptive Sampling Approach for the Reduced Basis Method. In: Realization and Model Reduction of Dynamical Systems – A Festschrift in Honor of 70th Birthday of Thanos Antoulas, pp. 137 - 155 (Eds. Beattie, C.; Benner, P.; Embree, M.; Gugercin, S.; Lefteriu, S.). Springer International Publishing, Cham (2022)

Benner, P.; Feng, L.: Model Order Reduction based on Moment-Matching. In: Model Order Reduction: Volume 1: System- and Data-Driven Methods and Algorithms, pp. 57 - 96 (Eds. Benner, P.; Grivet-Talocia, S.; Quarteroni, A.; Rozza, G.; Schilders, W. et al.). De Gruyter, Berlin, Boston (2021)

Chellappa, S.; Feng, L.; de la Rubia, V.; Benner, P.: Adaptive Interpolatory MOR by Learning the Error Estimator in the Parameter Domain. In: Model Reduction of Complex Dynamical Systems, pp. 97 - 117 (Eds. Benner, P.; Breiten, T.; Faßbender, H.; Hinze, M.; Stykel, T. et al.). Birkhäuser, Cham (2021)

Yue, Y.; Feng, L.; Meuris, P.; Schoenmaker, W.; Benner, P.: Application of Krylov-type Parametric Model Order Reduction in Efficient Uncertainty Quantification of Electro-thermal Circuit Models. In: Proceedings of the Progress In Electromagnetics Research Symposium (PIERS 2015), pp. 379 - 384. 36th Progress In Electromagnetics Research Symposium, Prague, Czech Republic, July 06, 2015 - July 09, 2015. (2015)

Banagaaya, N.; Feng, L.; Meuris, P.; Schoenmaker, W.; Benner, P.: Model Order Reduction of an Electro-Thermal Package Model. In IFAC-PapersOnLine, 48 (1), pp. 934 - 935. 8th Vienna International Conference on Mathematical Modelling, Vienna, Austria, February 18, 2015 - February 20, 2015. (2015)

Zhang, Y.; Feng, L.; Li, S.: An Efficient Output Error Bound for Model Order Reduction of Parametrized Evolution Equations. In IFAC-PapersOnLine, 48 (1), pp. 9 - 10. 8th Vienna International Conference on Mathematical Modelling MATHMOD, Vienna, Austria, February 18, 2015 - February 20, 2015. (2015)

Chellappa, S.; Feng, L.; Benner, P.: Accurate Error Estimation for Model Reduction of Nonlinear Dynamical Systems via Data-enhanced Error Closure. (2023)

Kapadia, H.; Feng, L.; Benner, P.: Active-Learning-Driven Surrogate Modeling for Efficient Simulation of Parametric Nonlinear Systems. (2023)

Sun, S.; Feng, L.; Chan, H. S.; Miličić, T.; Vidaković-Koch, T.; Benner, P.: Parametric Dynamic Mode Decomposition for Nonlinear Parametric Dynamical Systems. (2023)

Yue, Y.; Feng, L.; Benner, P.: An Adaptive Pole-Matching Method for Interpolating Reduced-Order Models. (2019)