@article{nokeyr,

title = {Data-driven aerodynamic shape design with distributionally robust optimization approaches},

author = {L. Chen, J. Rottmayer, L. Kusch, N. R.Gauger, Y. Ye, },

url = {https://doi.org/10.1016/j.cma.2024.117131},

issn = {0045-7825},

year  = {2024},

date = {2024-06-15},

urldate = {2024-06-15},

journal = {Computer Methods in Applied Mechanics and Engineering},

volume = {429},

pages = {117131},

abstract = {We formulate and solve data-driven aerodynamic shape design problems with distributionally robust optimization (DRO) approaches. DRO aims to minimize the worst-case expected performance in a set of distributions that is informed by observed data with uncertainties. Building on the findings of the work Gotoh, et al. (2018), we study the connections between a class of DRO and robust design optimization, which is classically based on the mean–variance (standard deviation) optimization formulation pioneered by Taguchi. Our results provide a new perspective to the understanding and formulation of robust design optimization problems. It enables data-driven and statistically principled approaches to quantify the trade-offs between robustness and performance, in contrast to the classical robust design formulation that captures uncertainty only qualitatively. Our preliminary computational experiments on aerodynamic shape optimization in transonic turbulent flow show promising design results.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{nokey,

title = {Adjoint-based design optimization of a Kenics static mixer},

author = {C.M. Ubal, N. Beishuizen, L. Kusch, J. van Oijen},

url = {https://doi.org/10.1016/j.rineng.2024.101856},

year  = {2024},

date = {2024-02-05},

urldate = {2024-02-05},

journal = {Results in Engineering},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{aehle_exploration_2023,

title = {Exploration of Differentiability in a Proton Computed Tomography Simulation Framework},

author = {M. Aehle, J. Alme, G. Barnaföldi, J. Blühdorn, T. Bodova, V. Borshchov, A. van den Brink, V. Eikeland, G. Feofilov, C. Garth, N. R. Gauger, et al.},

url = {https://iopscience.iop.org/article/10.1088/1361-6560/ad0bdd},

doi = {10.1088/1361-6560/ad0bdd},

year  = {2023},

date = {2023-11-10},

urldate = {2023-11-10},

journal = {Physics in Medicine and Biology},

volume = {68},

number = {24},

pages = {244002},

howpublished = {arXiv:2202.05551},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{KG2021,

title = {Robustness Measures for Multi-objective Robust Design},

author = {L. Kusch, N. R. Gauger},

url = {https://link.springer.com/chapter/10.1007/978-3-030-57422-2_12},

year  = {2021},

date = {2021-01-01},

journal = {Computational Methods in Applied Sciences},

volume = {55},

pages = {179-190},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{KuGa19,

title = {Robust Airfoil Design in the Context of Multi-objective Optimization},

author = {L. Kusch, N. R. Gauger},

url = {https://link.springer.com/chapter/10.1007/978-3-319-89988-6_23},

year  = {2019},

date = {2019-01-01},

journal = {Computational Methods in Applied Sciences},

volume = {48},

pages = {391-403},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{WalthKuschGauger2018,

title = {New Results for the Handling of Additional Equality Constraints in One-Shot Optimization},

author = {A. Walther and L. Kusch and N.R. Gauger},

url = {https://doi.org/10.1007/s10013-018-0306-y},

year  = {2018},

date = {2018-09-01},

journal = { Vietnam J. Math. },

volume = {46},

number = {4},

pages = {825-836},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{KAWG2018,

title = {A one-shot optimization framework with additional equality constraints applied to multi-objective aerodynamic shape optimization},

author = {L. Kusch and T. Albring and A. Walther and N.R. Gauger},

url = { https://doi.org/10.1080/10556788.2018.1437158},

year  = {2018},

date = {2018-03-02},

journal = {Optimization Methods and Software},

volume = {33},

number = {4-6},

pages = {694-707},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{KuGaPAMM2016,

title = {The One-Shot Method in SU2},

author = {L. Kusch and N.R. Gauger},

url = {http://onlinelibrary.wiley.com/doi/10.1002/pamm.201610338/epdf},

year  = {2016},

date = {2016-10-25},

journal = {Proc. Appl. Math. Mech.},

volume = {16},

number = {1},

pages = {699--700},

note = {DOI: 10.1002/pamm.201610338},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{WaGaKuRi2016,

title = {On an extension of one-shot methods to incorporate additional constraints},

author = {A. Walther and N. R. Gauger and L. Kusch and N. Richert},

url = {http://www.tandfonline.com/doi/abs/10.1080/10556788.2016.1146268?journalCode=goms20},

year  = {2016},

date = {2016-02-26},

journal = {Optimization Methods and Software},

volume = {31},

number = {3},

pages = {494-510},

note = {DOI:10.1080/10556788.2016.1146268},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Kusch2014efficient,

title = {Efficient Calculation of Pareto Optimal Points for Shape Optimization},

author = {L. Kusch and N.R. Gauger and M. Spiller},

isbn = {978-84-617-2141-2},

year  = {2014},

date = {2014-01-01},

journal = {Evolutionary and Deterministic Methods for Design, Optimization, and Control with Applications to Industrial and Societal Problems, EUROGEN 2013, Universidad de Las Palmas de Gran Canaria, Spain},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Koellermeier2012,

title = {Solving a non-linear partial differential equation for the simulation of tumour oxygenation},

author = {Julian Koellermeier, Lisa Kusch, Thorsten Lajewski},

url = {http://www.siam.org/students/siuro/vol5/S01136.pdf},

year  = {2012},

date = {2012-06-21},

journal = {SIAM Undergraduate Research Online (SIURO)},

volume = {5},

abstract = {This paper describes a novel approach to simulate tumor oxygenation which is very important because of its relevance for radiotherapy. In fact, it is considered to be one of the most important factors that determine the failure of radiation treatment. As former simulations were not able to deal with sufficiently large areas of tissue, we developed and investigated new methods in order to enable the use for real applications. The main work of this project includes the development of a new software to simulate tumor oxygenation. We therefore describe new methods to generate a realistic distribution of blood vessels inside the tumor tissue. After that, we come up with different discretization approaches for the vessels' boundaries. Finally, we overcome the problem of excessive memory storage by developing a new dedicated data format. Due to the reduction of memory consumption, we were able to simulate much larger domains with a finite difference method than with commercial software. In fact, it is now possible to calculate the oxygenation of tissues measuring several square centimeters in area.},

key = {10.1137/11S011365 },

note = {DOI:10.1137/11S011365},

keywords = {},

pubstate = {published},

tppubtype = {article}

}