A review on design of experiments and surrogate models in aircraft real-time and many-query aerodynamic analyses Raul Yondo a, * , Esther Andr es b , Eusebio Valero a a E.T.S.I. Aeron auticos, Universidad Polit ecnica de Madrid (UPM), Plaza Cardenal Cisneros 3, 28040 Madrid, Spain b Engineering Department, Ingeniera de Sistemas para la Defensa de Espa~ na S.A. (ISDEFE-INTA) & Universidad Polit ecnica de Madrid (UPM), Ctra. de Ajalvir Km. 4.5, 28850 Torrej on de Ardoz, Spain ARTICLE INFO Keywords: Sampling strategies Surrogate models Aircraft aerodynamics Aerodynamics design Surrogate-based optimization Industrial optimization ABSTRACT Full scale aerodynamic wind tunnel testing, numerical simulation of high dimensional (full-order) aerodynamic models or flight testing are some of the fundamental but complex steps in the various design phases of recent civil transport aircrafts. Current aircraft aerodynamic designs have increase in complexity (multidisciplinary, multi- objective or multi-fidelity) and need to address the challenges posed by the nonlinearity of the objective func- tions and constraints, uncertainty quantification in aerodynamic problems or the restrained computational budgets. With the aim to reduce the computational burden and generate low-cost but accurate models that mimic those full order models at different values of the design variables, Recent progresses have witnessed the intro- duction, in real-time and many-query analyses, of surrogate-based approaches as rapid and cheaper to simulate models. In this paper, a comprehensive and state-of-the art survey on common surrogate modeling techniques and surrogate-based optimization methods is given, with an emphasis on models selection and validation, dimen- sionality reduction, sensitivity analyses, constraints handling or infill and stopping criteria. Benefits, drawbacks and comparative discussions in applying those methods are described. Furthermore, the paper familiarizes the readers with surrogate models that have been successfully applied to the general field of fluid dynamics, but not yet in the aerospace industry. Additionally, the review revisits the most popular sampling strategies used in conducting physical and simulation-based experiments in aircraft aerodynamic design. Attractive or smart designs infrequently used in the field and discussions on advanced sampling methodologies are presented, to give a glance on the various efficient possibilities to a priori sample the parameter space. Closing remarks foster on future perspectives, challenges and shortcomings associated with the use of surrogate models by aircraft industrial aerodynamicists, despite their increased interest among the research communities. 1. Introduction In aircraft aerodynamic design teams, the computational burden linked with the preliminary or conceptual design phases is in general very prodigious and is characterized by high computational costs, high fidelities or sensitivity analyses. Identifying and screening multiple aircraft configurations (cruise/high lift, control surface deflections, etc) and flight conditions (Mach number, angle of attack, etc) in order to analyze the most promising ones require to generate fast and efficient methods. Commonly, high dimensional aerodynamic design models - HDAMs (discretization in more than 3 spatial dimensions), also know as full order aerodynamic models (FOAMs), require time consuming and computationally expensive simulations or physical experiments to evaluate the complex objective functions and constraints for analysis and optimization. Solving aerodynamic problems generally require real-time or many-query settings; a real-time analysis consists of instantaneous solutions under restricted resources and give the possibility to respond to evolving conditions as the phenomenon unfold (e.g. in routine analysis or control and nondestructive evaluation/parameter estimation). A many- query scenario arise when the FOAM is solved repeatedly for various configurations and design variables (e.g. in design optimization, optimal control or uncertainty analysis). As an example, while designing a new aircraft, a CFD (Computational Fluid Dynamics) campaign provides the aerodynamicists with flow solutions from only few selected flight con- ditions because it will be time-consuming and costly to evaluate all of them. To circumvent these burdens and enable a wider exploration of the * Corresponding author. E-mail addresses: yondo.raul@upm.es (R. Yondo), esther.andres@upm.es, eandres@isdefe.es (E. Andr es), eusebio.valero@upm.es (E. Valero). URL: http://www.airup-itn.eu Contents lists available at ScienceDirect Progress in Aerospace Sciences journal homepage: www.elsevier.com/locate/paerosci https://doi.org/10.1016/j.paerosci.2017.11.003 Received 30 March 2017; Received in revised form 29 November 2017; Accepted 30 November 2017 Available online xxxx 0376-0421/© 2017 Elsevier Ltd. All rights reserved. Progress in Aerospace Sciences xxx (2017) 1–39 Please cite this article in press as: R. Yondo, et al., A review on design of experiments and surrogate models in aircraft real-time and many-query aerodynamic analyses, Progress in Aerospace Sciences (2017), https://doi.org/10.1016/j.paerosci.2017.11.003