@conference {Huang_2020_Variational,
	title = {A Variational multiscale method with discontinuous subscales for output-based adaptation of aerodynamic flows},
	booktitle = {AIAA conference paper},
	number = {2020-1563},
	year = {2020},
	doi = {10.2514/6.2020-1563},
	author = {Arthur C. Huang and Hugh A. Carson and Steven R. Allmaras and Marshall C. Galbraith and David L. Darmofal and Dimitry S. Kamenetskiy}
}
@conference {Park_2019_Verification_of_Unstructured_Grid_Adaptation_Components,
	title = {Verification of unstructured grid adaptation components},
	booktitle = {AIAA conference paper},
	number = {2019{\textendash}1723},
	year = {2019},
	type = {AIAA Paper},
	doi = {10.2514/6.2019-1723},
	author = {Michael A. Park and Aravind Balan and W. Kyle Anderson and Marshall C. Galbraith and Philip Claude Caplan and Hugh A. Carson and Todd Michal and Joshua A. Krakos and Dmitry S. Kamenetskiy and Adrien Loseille and Fr{\'e}d{\'e}ric Alauzet and Lo{\"\i}c Frazza and Nicolas Barral}
}
@booklet {Vision_2030_Final_Report_CRDL,
	title = {CFD Vision 2030 Study: A Path to Revolutionary Computational Aerosciences},
	journal = {NASA Technical Report},
	number = {NASA/CR-2014-218178},
	year = {2014},
	author = {Slotnick, J P and Khodadoust, A and Alonso, J J and Darmofal, D L and Gropp, W D and Lurie, E A and Mavriplis, D J}
}
@article {Slotnick_2014_EnivornmentCFD,
	title = {Enabling the environmentally clean air transportation of the future: a vision of computational fluid dynamics in 2030},
	journal = {Philosophical transactions. Series A, Mathematical, physical, and engineering sciences},
	volume = {372},
	number = {2022},
	year = {2014},
	month = {08},
	pages = {20130317},
	abstract = {As global air travel expands rapidly to meet demand generated by economic growth, it is essential to continue to improve the efficiency of air transportation to reduce its carbon emissions and address concerns about climate change. Future transports must be {\textquoteleft}cleaner{\textquoteright}and designed to include technologies that will continue to lower engine emissions and reduce community noise. The use of computational fluid dynamics (CFD) will be critical to enable the design of these new concepts. In general, the ability to simulate aerodynamic and reactive flows using CFD has progressed rapidly during the past several decades and has fundamentally changed the aerospace design process. Advanced simulation capabilities not only enable reductions in ground-based and flight-testing requirements, but also provide added physical insight, and enable superior designs at reduced cost and risk. In spite of considerable success, reliable use of CFD has remained confined to a small region of the operating envelope due, in part, to the inability of current methods to reliably predict turbulent, separated flows. Fortunately, the advent of much more powerful computing platforms provides an opportunity to overcome a number of these challenges. This paper summarizes the findings and recommendations from a recent NASA-funded study that provides a vision for CFD in the year 2030, including an assessment of critical technology gaps and needed development, and identifies the key CFD technology advancements that will enable the design and development of much cleaner aircraft in the future.},
	isbn = {1364-503X; 1471-2962},
	doi = {10.1098/rsta.2013.0317},
	url = {http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4095895/},
	author = {Slotnick, J P and Khodadoust, A and Alonso, J J and Darmofal, D L and Gropp, W D and Lurie, E A and Mavriplis, D J and Venkatakrishnan, V}
}
@mastersthesis {Kudo_2014_SM,
	title = {Robust Adaptive High-Order {RANS} Methods},
	year = {2014},
	school = {Massachusetts Institute of Technology},
	type = {masters},
	address = {CDO},
	url = {http://hdl.handle.net/1721.1/95563},
	author = {Kudo, J}
}
@conference {Darmofal_2013_PXOverview,
	title = {An adaptive, higher-order discontinuous Galerkin finite element method for aerodynamics},
	booktitle = {AIAA conference paper},
	number = {2013-2871},
	year = {2013},
	author = {Darmofal, D L and Allmaras, S R and Yano, M and Kudo, J}
}
@conference {Krakos_2013_Anisotropic_Output-Based_Mesh_Optimization_Unsteady,
	title = {Anisotropic output-based mesh optimization for unsteady flows},
	booktitle = {AIAA conference paper},
	number = {2013-3083},
	year = {2013},
	author = {Krakos, J A and Darmofal, D L}
}
@article {Krakos_2012_Sensitivity_analysis_LCO,
	title = {Sensitivity analysis of limit cycle oscillations},
	journal = {Journal of Computational Physics},
	volume = {231},
	number = {8},
	year = {2012},
	pages = {3228 - 3245},
	abstract = {Many unsteady problems equilibrate to periodic behavior. For these problems the sensitivity of periodic outputs to system parameters are often desired, and must be estimated from a finite time span or frequency domain calculation. Sensitivities computed in the time domain over a finite time span can take excessive time to converge, or fail altogether to converge to the periodic value. Additionally, finite span outputs can exhibit local extrema in parameter space which the periodic outputs they approximate do not, hindering their use in optimization. We derive a theoretical basis for this error and demonstrate it using two examples, a van der Pol oscillator and vortex shedding from a low Reynolds number airfoil. We show that output windowing enables the accurate computation of periodic output sensitivities and may allow for decreased simulation time to compute both time-averaged outputs and sensitivities. We classify two distinct window types: long-time, over a large, not necessarily integer number of periods; and short-time, over a small, integer number of periods. Finally, from these two classes we investigate several examples of window shape and demonstrate their convergence with window size and error in the period approximation, respectively.},
	keywords = {Limit cycles, Periodic, Sensitivity analysis, Unsteady},
	issn = {0021-9991},
	doi = {10.1016/j.jcp.2012.01.001},
	url = {http://www.sciencedirect.com/science/article/pii/S0021999112000071},
	author = {Krakos, J A and Wang, Q and Hall, S R and Darmofal, D L}
}
@mastersthesis {Krakos_2012_PhD,
	title = {Unsteady Adjoint Analysis for Output Sensitivity and Mesh Adaptation},
	year = {2012},
	month = {September},
	school = {Massachusetts Institute of Technology},
	type = {phd},
	address = {Department of Aeronautics and Astronautics},
	url = {http://hdl.handle.net/1721.1/77133},
	author = {Krakos, J A}
}
@article {Krakos_2010_Effect_of_Small-Scale_Output_Unsteadiness_on_Adjoint-Based_Sensitivity,
	title = {Effect of small-scale output unsteadiness on adjoint-based sensitivity},
	journal = {AIAA Journal},
	volume = {48},
	number = {11},
	year = {2010},
	pages = {2611{\textendash}2623},
	doi = {10.2514/1.J050412},
	author = {Krakos, J A and Darmofal, D L}
}
@conference {Mavriplis_2007_Petaflop_Opportunities_for_NASA,
	title = {Petaflops opportunities for the {NASA} fundamental aeronautics program},
	booktitle = {AIAA conference paper},
	number = {2007-4084},
	year = {2007},
	author = {Mavriplis, D J and Darmofal, D L and Keyes, D E and Turner, M G}
}
@mastersthesis {Kountras_2004_SM,
	title = {Probabilistic Analysis of Turbine Blade Durability},
	year = {2004},
	school = {Massachusetts Institute of Technology},
	type = {masters},
	address = {Department of Aeronautics and Astronautics},
	url = {http://hdl.handle.net/1721.1/28893},
	author = {Kountras, A}
}
@article {Darmofal_2001_VortexCore1DModel,
	title = {Vortex core behaviour in confined and unconfined geometries: A quasi-one-dimensional model},
	journal = {Journal of Fluid Mechanics},
	volume = {449},
	year = {2001},
	pages = {61{\textendash}84},
	doi = {10.1017/S0022112001006103},
	author = {Darmofal, D L and Khan, R and Greitzer, E M and Tan, C S}
}
@mastersthesis {Kim_1998_SM,
	title = {An Adaptive Mesh Method for the Simulation of Blade Vortex Interaction},
	year = {1998},
	school = {Texas A\&M University},
	type = {masters},
	address = {Department of Aerospace Engineering},
	author = {Kim, K}
}
