@conference {Carson_2020_MOESS_CG_DG,
	title = {Mesh optimization via error sampling and synthesis: An update},
	booktitle = {AIAA conference paper},
	number = {2020-0087},
	year = {2020},
	doi = {10.2514/6.2020-0087},
	author = {Hugh A. Carson and Arthur C. Huang and Marshall C. Galbraith and Steven R. Allmaras and David L. Darmofal}
}
@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}
}
@article {Jayasinghe_2019_Distributed_Well_Model,
	title = {A discretization-independent distributed well model},
	journal = {Society of Petroleum Engineers Journal},
	year = {2019},
	month = {October},
	doi = {10.2118/198898-PA},
	author = {Jayasinghe, S. and Darmofal, D.L. and Dow, E. and Galbraith, M.C. and Allmaras, S.R.}
}
@conference {Frontin_2019_entropy_underresolved_DG,
	title = {Entropy behavior for underresolved discontinuous Galerkin discretization of the Navier-Stokes equations},
	booktitle = {AIAA conference paper},
	number = {2019{\textendash}1889},
	year = {2019},
	type = {AIAA Paper},
	doi = {10.2514/6.2019-1889},
	author = {Cory Frontin and David L. Darmofal and Steven R. Allmaras and Scott M. Murman}
}
@conference {Drela_2019_hybrid_shell_model,
	title = {Hybrid shell model for aeroelastic modeling},
	booktitle = {AIAA conference paper},
	number = {2019{\textendash}2227},
	year = {2019},
	type = {AIAA Paper},
	doi = {10.2514/6.2019-2227},
	author = {Mark Drela and Marshall Galbraith and Robert Haimes and Steven R. Allmaras and David L. Darmofal}
}
@conference {Zhang_2019_IBL2_free_transition,
	title = {A strongly-coupled non-parametric integral boundary layer method for aerodynamic analysis with free transition},
	booktitle = {AIAA conference paper},
	number = {2019-1154},
	year = {2019},
	doi = {10.2514/6.2019-1154},
	author = {Zhang, Shun and Drela, Mark and Allmaras, Steven R. and Galbraith, Marshall C. and Darmofal, David L.}
}
@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}
}
@article {Jayasinghe_2018_Adjoint_Analysis_BuckleyLeverett_TwoPhase,
	title = {Adjoint analysis of Buckley-Leverett and two-phase flow equations},
	journal = {Computational Geosciences},
	volume = {22},
	number = {2},
	year = {2018},
	month = {April},
	pages = {527{\textendash}542},
	author = {Jayasinghe, Savithru and Darmofal, David L. and Galbraith, Marshall C. and Burgess, Nicholas K. and Allmaras, Steven R.}
}
@conference {Galbraith_2018_SANS_RANS_3D_Benchmark,
	title = {SANS RANS solutions for 3D benchmark configurations},
	booktitle = {AIAA conference paper},
	number = {2018{\textendash}1570},
	year = {2018},
	type = {AIAA Paper},
	doi = {10.2514/6.2018-1570},
	author = {Marshall C. Galbraith and Steven R. Allmaras and David L. Darmofal}
}
@article {Jayasinghe_2017_Spacetime_Adaptive_Method_Reservoir_Flows_Formulation,
	title = {A space-time adaptive method for reservoir flows: Formulation and one-dimensional application},
	journal = {Computational Geosciences},
	volume = {22},
	year = {2018},
	month = {02/2018},
	pages = {107-123},
	chapter = {107},
	abstract = {<p>This paper presents a space-time adaptive framework for solving porous media flow problems, with specific application to reservoir simulation. A fully unstructured mesh discretization of space and time is used instead of a conventional time-marching approach. A space-time discontinuous Galerkin finite element method is employed to achieve a high-order discretization on the anisotropic, unstructured meshes. Anisotropic mesh adaptation is performed to reduce the error of a specified output of interest, by using a posteriori error estimates from the dual-weighted residual method to drive a metric-based mesh optimization algorithm. The space-time adaptive method is tested on a one-dimensional two-phase flow problem, and is found to be more efficient in terms of computational cost (degrees-of-freedom and total runtime) required to achieve a specified output error level, when compared to a conventional first-order time-marching finite volume method and the space-time discontinuous Galerkin method on structured meshes.</p>
},
	issn = {1573-1499},
	doi = {10.1007/s10596-017-9673-9},
	url = {http://dx.doi.org/10.1007/s10596-017-9673-9},
	author = {Jayasinghe, Y S and Darmofal, D L and Burgess, N K and Galbraith, M C and Allmaras, S R}
}
@conference {Huang_2019_Wellposed_NS_BCs,
	title = {Well-posed subsonic inflow/outflow boundary conditions for the Navier-Stokes equations},
	booktitle = {AIAA conference paper},
	number = {2018{\textendash}0361},
	year = {2018},
	type = {AIAA Paper},
	doi = {10.2514/6.2018-0361},
	author = {Arthur C. Huang and Steven R. Allmaras and Marshall C. Galbraith and David L. Darmofal}
}
@article {Ojeda_2017_AdaptiveCutCellConjugateHT,
	title = {An adaptive simplex cut-cell method for high-order discontinuous Galerkin discretizations of conjugate heat transfer problems},
	journal = {International Journal for Numerical Methods in Engineering},
	volume = {110},
	number = {4},
	year = {2017},
	pages = {350{\textendash}378},
	abstract = {In this paper, we present a solution framework for high-order discretizations of conjugate heat transfer problems on non-body-conforming meshes. The framework consists of and leverages recent developments in discontinuous Galerkin discretization, simplex cut-cell techniques, and anisotropic output-based adaptation. With the cut-cell technique, the mesh generation process is completely decoupled from the interface definitions. In addition, the adaptive scheme combined with the discontinuous Galerkin discretization automatically adjusts the mesh in each sub-domain and achieves high-order accuracy in outputs of interest. We demonstrate the solution framework through several multi-domained conjugate heat transfer problems consisting of laminar and turbulent flows, curved geometry, and highly coupled heat transfer regions. The combination of these attributes yield nonintuitive coupled interactions between fluid and solid domains, which can be difficult to capture with user-generated meshes. Copyright {\textcopyright} 2016 John Wiley \& Sons, Ltd.},
	keywords = {adaptation, conjugate heat transfer, cut cells, high-order},
	issn = {1097-0207},
	doi = {10.1002/nme.5362},
	url = {http://dx.doi.org/10.1002/nme.5362},
	author = {Ojeda, S M and Sun, H and Allmaras, S R and Darmofal, D L}
}
@article {Carson_2017_ErrorEstimation,
	title = {Analysis of output-based error estimation for finite element methods},
	journal = {Applied Numerical Mathematics},
	volume = {118},
	year = {2017},
	pages = {182 - 202},
	abstract = {Abstract In this paper, we develop a priori estimates for the convergence of outputs, output error estimates, and localizations of output error estimates for Galerkin finite element methods. Output error estimates for order p finite element solutions are constructed using the Dual-Weighted Residual (DWR) method with a higher-order p ' \&gt; p dual solution. Specifically, we analyze these \{DWR\} estimates for Continuous Galerkin (CG), Discontinuous Galerkin (DG), and Hybridized \{DG\} (HDG) methods applied to the Poisson problem. For all discretizations, as h {\textrightarrow} 0 , we prove that the output and output error estimate converge at order 2p and 2 p ' (assuming sufficient smoothness), while localizations of the output and output error estimate converge at 2 p + d and p + p ' + d . For DG, the results use a new post processing for the error associated with the lifting operator. For HDG, these rates improve an additional order when the stabilization is based upon an O ( 1 ) length scale.},
	keywords = {Hybridizable Discontinuous Galerkin},
	issn = {0168-9274},
	doi = {http://dx.doi.org/10.1016/j.apnum.2017.03.004},
	url = {http://www.sciencedirect.com/science/article/pii/S0168927417300648},
	author = {Carson, H A and Darmofal, D L and Galbraith, M C and Allmaras, S R}
}
@conference {Couchman_2017_FEMweakconvergence,
	title = {On the convergence of higher-order finite element methods to weak solutions},
	booktitle = {AIAA conference paper},
	number = {2017-4274},
	year = {2017},
	keywords = {finite element methods},
	doi = {10.2514/6.2017-4274},
	author = {Couchman, B L and Darmofal, D L and Allmaras, S R and Galbraith, M C}
}
@conference {Zhang_2017_IBL_DG,
	title = {A non-parametric discontinuous Galerkin formulation of the integral boundary layer equations with strong viscous/inviscid coupling},
	booktitle = {AIAA conference paper},
	number = {2017-4278},
	year = {2017},
	keywords = {finite element methods, integral boundary layer methods},
	doi = {10.2514/6.2017-4278},
	author = {Zhang, S and Galbraith, M C and Allmaras, S R and Drela, M and Darmofal, D L}
}
@article {Hu_2016_turbmodelcases_AIAAJ,
	title = {Application of Higher-order Adaptive Method to Reynolds-Averaged Navier{\textendash}Stokes Test Cases},
	journal = {AIAA Journal},
	volume = {54},
	number = {9},
	year = {2016},
	doi = {10.2514/1.J054558},
	author = {Hu, Y and Wagner, C F and Allmaras, S R and Galbraith, M C and Darmofal, D L}
}
@conference {Galbraith_2015_Verification_CFD_Development,
	title = {A verification driver process for rapid development of CFD software},
	booktitle = {AIAA conference paper},
	number = {2015-0818},
	year = {2015},
	doi = {10.2514/6.2015-0818},
	author = {Galbraith, M C, and Allmaras, S R, and Darmofal, D L}
}
@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}
}
@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}
}
