Enhanced multi-fidelity model for flight simulation using global exploration and the Kriging method

Using the global exploration and Kriging-based multi-fidelity analysis methods, this study developed a multi-fidelity aerodynamic database for use in the performance analysis of flight vehicles and for use in flight simulations. Athena vortex lattice, a program based on vortex lattice method, was used as the low-fidelity analysis tool in the multi-fidelity analysis method. The in-house high-fidelity AADL-3D code was based on the Navier–Stokes equations. The AADL-3D code was validated by comparing the data and the analysis results of the Onera M-6 wing and NACA TN 3649. The design of experiment method and the Kriging method were applied to integrate low- and high-fidelity analysis results. General data tendencies were established from the low-fidelity analysis results. The high-fidelity analysis results and the Kriging method were used to generate a surrogate model, from which the low-fidelity analysis results were interpolated. To reduce repeated calculations, three design points were simultaneously added for each calculation. The convergence of three design points was avoided by considering only the peak points as additional design points. The reliability of the final surrogate model was determined by applying the leave-one-out cross-validation method and by obtaining the cross-validation root mean square error. Using the multi-fidelity model developed in this study, a multi-fidelity aerodynamic database was constructed for use in the three degrees of freedom flight simulation of flight vehicles.

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Efficient Flight Simulation Using Kriging Surrogate Model Based Aerodynamic Database

53rd AIAA Aerospace Sciences Meeting ◽

10.2514/6.2015-0543 ◽

2015 ◽

Cited By ~ 1

Author(s):

Norazila Othman ◽

Masahiro Kanazaki

Keyword(s):

Surrogate Model ◽

Flight Simulation ◽

Kriging Surrogate Model ◽

Model Based ◽

Aerodynamic Database

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A Multiobjective Adaptive Surrogate Modeling-Based Optimization (MO-ASMO) Framework Using Efficient Sampling Strategies

Volume 2B: 43rd Design Automation Conference ◽

10.1115/detc2017-67541 ◽

2017 ◽

Cited By ~ 3

Author(s):

Yong Hoon Lee ◽

R. E. Corman ◽

Randy H. Ewoldt ◽

James T. Allison

Keyword(s):

Surrogate Model ◽

Design Space ◽

Surrogate Modeling ◽

Pareto Set ◽

Test Problems ◽

High Fidelity ◽

Sampling Strategies ◽

Nsga Ii ◽

Sample Points ◽

Fidelity Model

A novel multiobjective adaptive surrogate modeling-based optimization (MO-ASMO) framework is proposed to utilize a minimal number of training samples efficiently for sequential model updates. All the sample points are enforced to be feasible, and to provide coverage of sparsely explored sparse design regions using a new optimization subproblem. The MO-ASMO method only evaluates high-fidelity functions at feasible sample points. During an exploitation sample phase, samples are selected to enhance solution accuracy rather than the global exploration. Sampling tasks are especially challenging for multiobjective optimization; for an n-dimensional design space, a strategy is required for generating model update sample points near an (n − 1)-dimensional hypersurface corresponding to the Pareto set in the design space. This is addressed here using a force-directed layout algorithm, adapted from graph visualization strategies, to distribute feasible sample points evenly near the estimated Pareto set. Model validation samples are chosen uniformly on the Pareto set hypersurface, and surrogate model estimates at these points are compared to high-fidelity model responses. All high-fidelity model evaluations are stored for later use to train an updated surrogate model. The MO-ASMO algorithm, along with the set of new sampling strategies, are tested using two mathematical and one realistic engineering problems. The second mathematical test problems is specifically designed to test the limits of this algorithm to cope with very narrow, non-convex feasible domains. It involves oscillatory objective functions, giving rise to a discontinuous set of Pareto-optimal solutions. Also, the third test problem demonstrates that the MO-ASMO algorithm can handle a practical engineering problem with more than 10 design variables and black-box simulations. The efficiency of the MO-ASMO algorithm is demonstrated by comparing the result of two mathematical problems to the results of the NSGA-II algorithm in terms of the number of high fidelity function evaluations, and is shown to reduce total function evaluations by several orders of magnitude when converging to the same Pareto sets.

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Selection of Existing Sail Designs for Multi-Fidelity Surrogate Models

Journal of Sailing Technology ◽

10.5957/jst/2022.7.2.31 ◽

2022 ◽

Vol 7 (01) ◽

pp. 31-51

Author(s):

Tanya Peart ◽

Nicolas Aubin ◽

Stefano Nava ◽

John Cater ◽

Stuart Norris

Keyword(s):

Surrogate Model ◽

Lift Coefficient ◽

Simulation Method ◽

Surrogate Models ◽

High Fidelity ◽

Data Points ◽

Velocity Prediction ◽

The Difference ◽

Fidelity Model ◽

Selection Of

Velocity Prediction Programs (VPPs) are commonly used to help predict and compare the performance of different sail designs. A VPP requires an aerodynamic input force matrix which can be computationally expensive to calculate, limiting its application in industrial sail design projects. The use of multi-fidelity kriging surrogate models has previously been presented by the authors to reduce this cost, with high-fidelity data for a new sail being modelled and the low-fidelity data provided by data from existing, but different, sail designs. The difference in fidelity is not due to the simulation method used to obtain the data, but instead how similar the sail’s geometry is to the new sail design. An important consideration for the construction of these models is the choice of low-fidelity data points, which provide information about the trend of the model curve between the high-fidelity data. A method is required to select the best existing sail design to use for the low-fidelity data when constructing a multi-fidelity model. The suitability of an existing sail design as a low fidelity model could be evaluated based on the similarity of its geometric parameters with the new sail. It is shown here that for upwind jib sails, the similarity of the broadseam between the two sails best indicates the ability of a design to be used as low-fidelity data for a lift coefficient surrogate model. The lift coefficient surrogate model error predicted by the regression is shown to be close to 1% of the lift coefficient surrogate error for most points. Larger discrepancies are observed for a drag coefficient surrogate error regression.

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Accelerating the estimation of collisionless energetic particle confinement statistics in stellarators using multifidelity Monte Carlo

Nuclear Fusion ◽

10.1088/1741-4326/ac4777 ◽

2021 ◽

Author(s):

Frederick Law ◽

Antoine J Cerfon ◽

Benjamin Peherstorfer

Keyword(s):

Monte Carlo ◽

Surrogate Model ◽

Energetic Particle ◽

Small Time ◽

Point Of View ◽

High Fidelity ◽

Monte Carlo Studies ◽

Long Time ◽

Particle Confinement ◽

Fidelity Model

Abstract In the design of stellarators, energetic particle confinement is a critical point of concern which remains challenging to study from a numerical point of view. Standard Monte Carlo analyses are highly expensive because a large number of particle trajectories need to be integrated over long time scales, and small time steps must be taken to accurately capture the features of the wide variety of trajectories. Even when they are based on guiding center trajectories, as opposed to full-orbit trajectories, these standard Monte Carlo studies are too expensive to be included in most stellarator optimization codes. We present the first multifidelity Monte Carlo scheme for accelerating the estimation of energetic particle confinement in stellarators. Our approach relies on a two-level hierarchy, in which a guiding center model serves as the high-fidelity model, and a data-driven linear interpolant is leveraged as the low-fidelity surrogate model. We apply multifidelity Monte Carlo to the study of energetic particle confinement in a 4-period quasi-helically symmetric stellarator, assessing various metrics of confinement. Stemming from the very high computational efficiency of our surrogate model as well as its sufficient correlation to the high-fidelity model, we obtain speedups of up to 10 with multifidelity Monte Carlo compared to standard Monte Carlo.

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Adaptive response prediction for aerodynamic shape optimization

Engineering Computations ◽

10.1108/ec-02-2016-0070 ◽

2017 ◽

Vol 34 (5) ◽

pp. 1485-1500

Author(s):

Leifur Leifsson ◽

Slawomir Koziel

Keyword(s):

Shape Optimization ◽

Adaptive Response ◽

Simulation Models ◽

Response Prediction ◽

High Fidelity ◽

High Fidelity Simulation ◽

Aerodynamic Shape Optimization ◽

Content Type ◽

Aerodynamic Shape ◽

Fidelity Model

Purpose The purpose of this paper is to reduce the overall computational time of aerodynamic shape optimization that involves accurate high-fidelity simulation models. Design/methodology/approach The proposed approach is based on the surrogate-based optimization paradigm. In particular, multi-fidelity surrogate models are used in the optimization process in place of the computationally expensive high-fidelity model. The multi-fidelity surrogate is constructed using physics-based low-fidelity models and a proper correction. This work introduces a novel correction methodology – referred to as the adaptive response prediction (ARP). The ARP technique corrects the low-fidelity model response, represented by the airfoil pressure distribution, through suitable horizontal and vertical adjustments. Findings Numerical investigations show the feasibility of solving real-world problems involving optimization of transonic airfoil shapes and accurate computational fluid dynamics simulation models of such surfaces. The results show that the proposed approach outperforms traditional surrogate-based approaches. Originality/value The proposed aerodynamic design optimization algorithm is novel and holistic. In particular, the ARP correction technique is original. The algorithm is useful for fast design of aerodynamic surfaces using high-fidelity simulation data in moderately sized search spaces, which is challenging using conventional methods because of excessive computational costs.

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A Language-Oriented Analysis of Situation Awareness in Pilots in High-Fidelity Flight Simulation

Communications in Computer and Information Science - HCI International 2020 – Late Breaking Posters ◽

10.1007/978-3-030-60703-6_82 ◽

2020 ◽

pp. 639-646

Author(s):

Alexia Ziccardi ◽

Kathleen Van Benthem ◽

Chris M. Herdman

Keyword(s):

Situation Awareness ◽

Flight Simulation ◽

High Fidelity

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High Fidelity Microsurgical Simulation: The Thiel Model and Evaluation Instrument

Plastic Surgery ◽

10.1177/2292550318800324 ◽

2018 ◽

Vol 27 (2) ◽

pp. 118-124 ◽

Cited By ~ 1

Author(s):

Andrei Odobescu ◽

Isak Goodwin ◽

Djamal Berbiche ◽

Joseph BouMerhi ◽

Patrick G. Harris ◽

...

Keyword(s):

External Validity ◽

Internal Validity ◽

High Fidelity ◽

Evaluation Instrument ◽

Intra Class Correlation ◽

Validity Measures ◽

The Difference ◽

Fidelity Model ◽

Junior Residents ◽

Internal And External Validity

Background: The Thiel embalmment method has recently been used in a number of medical simulation fields. The authors investigate the use of Thiel vessels as a high fidelity model for microvascular simulation and propose a new checklist-based evaluation instrument for microsurgical training. Methods: Thirteen residents and 2 attending microsurgeons performed video recorded microvascular anastomoses on Thiel embalmed arteries that were evaluated using a new evaluation instrument (Microvascular Evaluation Scale) by 4 fellowship trained microsurgeons. The internal validity was assessed using the Cronbach coefficient. The external validity was verified using regression models. Results: The reliability assessment revealed an excellent intra-class correlation of 0.89. When comparing scores obtained by participants from different levels of training, attending surgeons and senior residents (Post Graduate Year [PGY] 4-5) scored significantly better than junior residents (PGY 1-3). The difference between senior residents and attending surgeons was not significant. When considering microsurgical experience, the differences were significant between the advanced group and the minimal and moderate experience groups. The differences between minimal and moderate experience groups were not significant. Based on the data obtained, a score of 8 would translate into a level of microsurgical competence appropriate for clinical microsurgery. Conclusions: Thiel cadaveric vessels are a high fidelity model for microsurgical simulation. Excellent internal and external validity measures were obtained using the Microvascular Evaluation Scale (MVES).

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Effect of control surfaces on the aerodynamic database of the Stratofly hypersonic vehicle

MATEC Web of Conferences ◽

10.1051/matecconf/201930402021 ◽

2019 ◽

Vol 304 ◽

pp. 02021

Author(s):

Andrea Flora ◽

Pasquale Capasso ◽

Simona Brancaccio ◽

Paolo Ambrico ◽

Alessio D’Onofrio ◽

...

Keyword(s):

Vortex Lattice ◽

Free Stream ◽

Aerodynamic Coefficients ◽

Horizon 2020 ◽

Wide Range ◽

Aerodynamic Database ◽

Two Dimensional Flow ◽

Research Goal ◽

Expansion Theory ◽

Control Surfaces

This paper aims at studying the control surfaces of the STRATOFLY project reference aircraft, funded by the European Commission, under the framework of Horizon 2020 plan. The values of aerodynamic coefficients in a wide range of flow free-stream conditions are stored in the aircraft aerodynamic database. The research goal is to update a pre-existent database that was developed with fixed control surfaces using the six control surfaces deflection as input. Different Mach numbers determine different flow regimes: subsonic, transonic, supersonic, and hypersonic. In subsonic, transonic and low supersonic regimes a vortex-lattice solver is used to obtain the global coefficients assuming an unviscous flow on a simplified model. In hypersonic flow a build-up approach is applied: the control surfaces deflection contribution is developed by assuming a two-dimensional flow on the airfoil and by applying shock-expansion theory on the geometry. Then the paper analyses results showing stability and L/D results. The final paragraph focuses on trimmability at cruise Mach. No trimmed solution is obtainable to optimize the propulsive system. The solution proposed to solve this issue is to extend the four elevons: larger elevons are found to be able to trim the vehicle at the desired angle of attack.

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Real time model-based diagnosis enabled by hybrid modeling

Annual Conference of the PHM Society ◽

10.36001/phmconf.2020.v12i1.1278 ◽

2020 ◽

Vol 12 (1) ◽

pp. 10

Author(s):

Ion Matei ◽

Alexander Feldman ◽

Johan De Kleer ◽

Alexandre Perez

Keyword(s):

Automatic Differentiation ◽

Complex Model ◽

Hybrid Modeling ◽

High Fidelity ◽

Time Model ◽

Order Of Magnitude ◽

Switch System ◽

Using Data ◽

Model Components ◽

Fidelity Model

In this paper we propose a hybrid modeling approach for generating reduced models of a high fidelity model of a physical system. We propose machine learning inspired representations for complex model components. These representations preserve in part the physical interpretation of the original components. Training platforms featuring automatic differentiation are used to learn the parameters of the new representations using data generated by the high-fidelity model. We showcase our approach in the context of fault diagnosis for a rail switch system. We generate three new model abstractions whose complexities are two order of magnitude smaller than the complexity of the high fidelity model, both in the number of equations and simulation time. Faster simulations ensure faster diagnosis solutions and enable the use of diagnosis algorithms relying heavily on large numbers of model simulations.

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