Engineering topics

Stanford, Bret K.

Publications and source records attributed to Stanford, Bret K..

At least 19 records

NASA NTRS2020

Optimal Aircraft Control Surface Layouts for Maneuver and Gust Load Alleviation

The goal of this work is to conduct aeroservoelastic optimization of a high aspect ratio transport wingbox with distributed control surfaces along the trailing edge. The control surfaces are utilized for both quasi-steady maneuver load alleviation (MLA) and unsteady gust load alleviation (GLA). The optimizer dictates the sizing details of the wingbox, the steady and unsteady control surface rotations, and also the control surface layout. Layout design variables specifically dictate which control surfaces to retain, and which to remove. The objective function is to minimize the sum of the actuator weight and the structural weight, with several imposed constraints related to structural failure and actuator saturation. The optimizer’s preferences with regards to control surface layout for MLA are in strong contrast to GLA-driven designs. The GLA-driven design space also suffers from local minima not evident in the MLA space.

Stanford, Bret K.↗

NASA NTRS2020

Static Loads Testing of a High Aspect Ratio Tow-Steered Wingbox

Static loads testing was performed on a 39-foot, high-aspect-ratio wingbox comprising carbon fiber tow-steered wing skins that were tailored for aircraft fuel efficiency under aeroelastic loads. The test article was designated the Passive Aeroelastic Tailored (PAT) wing. To date, the PAT wing, which has an aspect ratio of 13.5, is the largest wingbox designed and built to employ variably oriented carbon fibers along the span of the wing. During testing, distributed point loads were applied to the wingbox to simulate both -1g and 2.5g maneuver loads. To determine the wingbox’s flexural axis location, individual point loads were applied. The global response of the wing (displacement and rotation measurements) showed similar trends compared to the finite element model predictions, though discrepancies of up to 17% were observed when comparing actual values between model and test. It was concluded that the boundary conditions and nonstructural features of the wingbox were the likely cause of the inconsistencies. The local response of the wingbox (strain measurements), which was much less affected by factors unrelated to tow-steering, exhibited good agreement with the model predictions, validating the modelling techniques employed for tow-steered composites.

Tow-steered composites↗

NASA NTRS2019

Preliminary Nonlinear Structural Analysis of Advanced Composite Tow-Steered Shells with Large Geometric Imperfections

The structural performance of two advanced composite tow-steered shells with and without tow overlaps, and with large geometric imperfections, are predicted using linear and geometrically nonlinear finite element analyses. These shells, 35 in. long and approximately 16.3 in. diameter, are fabricated using automated fiber placement from IM7/8552 graphite/epoxy prepreg. The 8-ply,[±45/±Θ]s. shell layup incorporates a steered fiber angle Θ that varies from 10 deg. to 45 deg. periodically over the shell circumference. Shell analysis models are evaluated using geometric imperfections normalized to ±1 shell wall thickness (±0.040 in.), which are then superposed and rotated incrementally around the shell longitudinal axis. Using these nominal imperfections, the shell prebuckling axial stiffnesses and buckling loads predicted with linear and nonlinear analyses are close to reference values from linear analyses with no imperfections. The linear and nonlinear analyses are then repeated for scaled imperfections that are larger by up to a factor of 10. For these larger imperfections, linear analyses predict reductions in axial stiffnesses and buckling loads of up to 5 and 30 percent, respectively, from reference values. The nonlinear analyses predict even larger reductions in axial stiffnesses and buckling loads of up to 10 and 55 percent, respectively.

Dobrin, Calvin P.↗

NASA NTRS2019

Active Flutter Suppression Using Reduced-Order Modeling for Transonic Aeroservoelastic Control Law Development

In this paper, several aerodynamic reduced-order models (ROMs) are generated and coupled with structural models to form aeroelastic ROMs. The aerodynamic ROMs generated here include the effects of control surface motion and are appropriate for use in aeroservoelastic applications. Simple observer-based full-state feedback controllers were designed from these aeroelastic ROMs. Additionally, observer gain matrices were designed from and coupled to the aeroelastic ROMs. Each (linear) observer was then used to estimate the dynamics of a (nonlinear) stand-alone computational fluid-structure dynamics simulation. Then, using the estimated states and the full-state feedback controller, control surface commands were fed back into the computational fluid-structure dynamics simulation to successfully achieve active flutter suppression. The process, as well as some results, are presented in this paper.

Waite, Josiah M.↗

NASA NTRS2019

Whirl Flutter and the Development of the NASA X-57 Maxwell

The X-57 Maxwell is NASA’s all-electric demonstration vehicle. The primary demonstration objective of this flight test program is to show a factor of five reduction in energy consumption. The vehicle includes two large wing tip propellers designed to provide propul- sion at cruise conditions and twelve leading edge propellers designed to operate at high lift conditions. The first configuration of the vehicle that will be flight tested has the large wing tip propellers relocated to an inboard wing station. A simplified structural dynamic model of the propulsion system has been generated and coupled with a beam model of the vehicle. Whirl flutter analyses have been performed, examining the stability of the isolated propulsion system and coupled to the beam model of the vehicle. Trimmed flight scenarios for the vehicle include straight and level flight and zero power windmilling conditions. The whirl flutter analyses for this configuration indicate that the configuration will be free of whirl flutter within the required flight envelope.

Heeg, Jennifer↗

NASA NTRS2019

Sizing and Topology Design of an Aeroelastic Wingbox Under Uncertainty

The goals of this work are to use a nested optimizer to conduct simultaneous sizing (inner level) and topology (outer level) design of a wingbox, considering uncertainties in the safety factors used to define the aeroelastic constraints. These uncertainties, propagated via sampling-driven polynomial chaos, are explicitly introduced at the inner level of the method, during gradient-based sizing optimization, resulting in a stochastic optimal sizing distribution. Measures of robustness in the total structural mass are then passed to the outer level, where a global optimizer evolves the topology parameters. The results demonstrate design choices needed to improve robustness in the face of uncertain safety factors, and the various physical mechanisms driving this process.

Stanford, Bret K.↗

NASA NTRS2019

A Mixed Integer Efficient Global Optimization Algorithm with Multiple Infill Strategy - Applied to a Wing Topology Optimization Problem

With the advancement in high performance computing and numerical optimization techniques,engineering design optimization problems are becoming more complex, larger scale,higher fidelity, and computationally more demanding, requiring longer run times than ever before. There exists methodologies and techniques that can address some of these challenges but very few can address all, and most are limited in the extent that these concerns can be addressed. With the goal of addressing such challenging engineering problems, we developed anew optimization framework, named AMIEGO, that combines concepts from surrogate-based optimization approaches, gradient-based numerical methods, Partial Least Squares, evolutionary algorithms, and Branch-and-Bound, providing newer capabilities that were not previouslyperceived. However, the original version of this framework, in the process of adaptive samplingto explore and exploit the design space, finds only a single sample point per iteration. The efforthere builds upon this previously developed optimization framework to include multiple infillsampling capability that combines the concept of generalized expected improvement function,unsupervised learning, and multi-objective evolutionary technique. To demonstrate, AMIEGOwith the multiple infill capability (called AMIEGO-MIMOS) solves a series of increasingly difficultengineering design optimization problems. The results reveal the performance of the newapproach is problem dependent. When applied to a ten-bar truss problem, the newly proposedmultiple infill strategy consistently leads to a better design solutions when compared to theexisting CPTV method (implemented with the context of the AMIEGO framework). On theother hand, when applied to a mixed-integer high fidelity wing topology optimization problem- MIMOS, despite showing a steeper convergence at the start, eventually leads to an inferiorsolution as compared to CPTV approach. These results also reveal that a small number ofstarting points, in general, are sufficient to lead to a good overall solution.

Mixed-integer optimization↗

NASA NTRS2019

Performance Enhancement of the Flexible Transonic Truss-Braced Wing Aircraft Using Variable-Camber Continuous Trailing-Edge Flaps

Aircraft designers are to a growing extent using vehicle flexibility to optimize performance with objectives such as gust load alleviation and drag minimization. More complex aerodynamically optimized configurations may also require dynamic loads and perhaps eventually flutter suppression. This paper considers an aerodynamically optimized truss-braced wing aircraft designed for a Mach 0.745 cruise. The variable camber continuous trailing edge flap concept with a feedback control system is used to enhance aeroelastic stability. A linearized reduced order aerodynamic model is developed from unsteady Reynolds averaged Navier-Stokes simulations. A static output feedback controller is developed from that model. Closed-loop simulations using the reduced order aerodynamic model show that the controller is effective in stabilizing the vehicle dynamics.

Bartels, Robert E.↗

NASA NTRS2019

Reduced Order Modeling for Transonic Aeroservoelastic Control Law Development

As aircraft become more flexible, aeroelastic considerations become increasingly important and complex, particularly for transonic flight where nonlinearities in the flow render linear analysis tools less effective. In order to analyze these aeroelastic interactions between the fluid and the structure efficiently, reduced order models (ROMs) are sometimes generated from and used in place of computational fluid dynamics solutions. In this paper, several aerodynamic ROMs are generated and coupled with structural models to form aeroelastic ROMs. The aerodynamic ROMs generated here include the effects of control surface motion. Hence, the aeroelastic ROMs presented here are appropriate for use in aeroservoelastic applications and are intended to be used for aeroservoelastic control law development. These ROMs are used to simulate a number of test cases with and without control surface involvement. Results show that several of the ROMs generated in the paper are able to predict results similar to solutions of higher-order computational methods.

Waite, Josiah M.↗

NASA NTRS2019

Gradient-Based Aeroservoelastic Optimization with Static Output Feedback

Static output feedback considers an optimal low-order feedback matrix which directly connects the sensors to the control inputs. This work demonstrates the numerical techniques needed to compute the analytical gradient of the optimal feedback matrix with respect to design variables, which may then be used for gradient-based optimization. The derivatives are demonstrated for aeroservoelastic optimization under a series of closed- loop gust load alleviation constraints, considering a continuous stochastic gust load applied to a transport vehicle configuration, among other design constraints such as utter and maneuver loads. The optimal trade-o s between passive load alleviation and active load alleviation for static output feedback are compared with those from full-state feedback, which may be considered an upper-bound for effective sensor-based control.

Stanford, Bret K.↗

NASA NTRS2018

Active Flutter Suppression Controllers Derived from Linear and Nonlinear Aerodynamics: Application to a Transport Aircraft Model

Active flutter suppression has been demonstrated in simulation by many researchers, generally using methods based on linear aerodynamics and often with simplistic geometries. In this paper, active flutter suppression is demonstrated in a simulation using a Navier-Stokes aerodynamics code, FUN3D (Fully Unstructured Navier-Stokes Three-Dimensional), and a realistic transport aircraft configuration. This is accomplished using simple observer-feedback controllers derived from linear aeroelastic models, including reduced order models built via FUN3D data. The development of these reduced order models is described here. It is shown that controllers derived from reduced order models of the nonlinear aerodynamics outperform controllers based on linear aerodynamics.

Waite, Josiah M.↗

NASA NTRS2018

Aeroservoelastic Optimization under Stochastic Gust Constraints

This work considers the aeroservoelastic optimization of a highly flexible transport aircraft wingbox with several control surfaces distributed along the trailing edge. The steady deflections of the control surfaces are designed to alleviate static maneuver loads, while the unsteady deflections are designed to alleviate stochastic continuous gust disturbances. Spatially-detailed unsteady stochastic stress and panel buckling constraints are formulated via modal acceleration, and by methods to locate the most-probable failure point along an equal-probability hypersurface. For the case considered here, it is found that the inclusion of such gust constraints during optimization presents a sizable structural mass penalty. In some cases, this mass penalty can be completely recovered with controlled gust load alleviation.

Stanford, Bret K.↗

NASA NTRS2018

Status Report on Aeroelasticity in the Vehicle Development for X-57 Maxwell

Risk reduction is the objective of the X-57 Maxwell aeroelasticity team. The X-57, NASA’s experimental electric propulsion aircraft, has a long thin wing with primary propulsion systems located at the wing tips and high lift motors distributed along the span. Many of the classical aeroelastic concerns associated with such a configuration were addressed through early design decisions. The as-designed intermediate flight vehicle configurations show flutter mechanisms associated with flexible models of control surface systems –the stabilator, flaps and ailerons. Improvements to the analytical models, based on ground test data and project decisions about flight operations, show improved prospects of the vehicle being aeroelastically stable throughout the flight envelope. On-going ground testing and further analyses will lend credibility to the flutter predictions and vehicle safety.

Heeg, Jennifer↗

NASA NTRS2018

Sizing and Layout Design of an Aeroelastic Wingbox Through Nested Optimization

The goals of this work are to 1) develop an optimization algorithm that can simultaneously handle a large number of sizing variables and topological layout variables for an aeroelastic wingbox optimization problem and 2) utilize this algorithm to ascertain the benefits of curvilinear wingbox components. The algorithm used here is a nested optimization, where the outer level optimizes the rib and skin stiffener layouts with a surrogate-based optimizer, and the inner level sizes all of the components via gradient-based optimization. Two optimizations are performed: one restricted to straight rib and stiffener components only, the other allowing curved members. A moderate 1.18% structural mass reduction is obtained through the use of curvilinear members.

Stanford, Bret K.↗

NASA NTRS2017

Economical Unsteady High-Fidelity Aerodynamics for Structural Optimization with a Flutter Constraint

Structural optimization with a flutter constraint for a vehicle designed to fly in the transonic regime is a particularly difficult task. In this speed range, the flutter boundary is very sensitive to aerodynamic nonlinearities, typically requiring high-fidelity Navier-Stokes simulations. However, the repeated application of unsteady computational fluid dynamics to guide an aeroelastic optimization process is very computationally expensive. This expense has motivated the development of methods that incorporate aspects of the aerodynamic nonlinearity, classical tools of flutter analysis, and more recent methods of optimization. While it is possible to use doublet lattice method aerodynamics, this paper focuses on the use of an unsteady high-fidelity aerodynamic reduced order model combined with successive transformations that allows for an economical way of utilizing high-fidelity aerodynamics in the optimization process. This approach is applied to the common research model wing structural design. As might be expected, the high-fidelity aerodynamics produces a heavier wing than that optimized with doublet lattice aerodynamics. It is found that the optimized lower skin of the wing using high-fidelity aerodynamics differs significantly from that using doublet lattice aerodynamics.

Bartels, Robert E.↗

NASA NTRS2017

Aeroelastic Wingbox Stiffener Topology Optimization

This work considers an aeroelastic wingbox model seeded with run-out blade stiffeners along the skins. Topology optimization is conducted within the shell webs of the stiffeners, in order to add cutouts and holes for mass reduction. This optimization is done with a global-local approach in order to moderate the computational cost: aeroelastic loads are computed at the wing-level, but the topology and sizing optimization is conducted at the panel-level. Each panel is optimized separately under stress, buckling, and adjacency constraints, and periodically reassembled to update the trimmed aeroelastic loads. The resulting topology is baselined against a design with standard full-depth solid stiffener blades, and found to weigh 7.43% less.

Stanford, Bret K.↗

NASA NTRS2017

Whirl Flutter Stability and Its Influence on the Design of the Distributed Electric Propeller Aircraft X- 57

This paper studies the whirl flutter stability of the NASA experimental electric propulsion aircraft designated the X-57 Maxwell. whirl flutter stability is studied at two flight conditions: sea level at 2700 RPM to represent take-off and landing and 8000 feet at 2250 RPM to represent cruise. Two multibody dynamics analyses are used: CAMRAD II and Dymore. The CAMRAD II model is a semi-span X-57 model with a modal representation for the wing/pylon system. The Dymore model is a semi-span wing with a propeller composed of beam elements for the wing/pylon system that airloads can be applied to. The two multibody dynamics analyses were verified by comparing structural properties between each other and the NASTRAN analysis. For whirl flutter, three design revisions of the wing and pylon mount system are studied. The predicted frequencies and damping ratio of the wing modes show good agreements between the two analyses. Dymore tended to predict a slightly lower damping ratio as velocity increased for all three dynamic modes presented. Whirl flutter for the semi-span model was not present up to 500 knots for the latest design, well above the operating range of the X-57.

Hoover, Christian B.↗

NASA NTRS2017

Uncertainty Quantification of the FUN3D-Predicted NASA CRM Flutter Boundary

A nonintrusive point collocation method is used to propagate parametric uncertainties of the flexible Common Research Model, a generic transport configuration, through the unsteady aeroelastic CFD solver FUN3D. A range of random input variables are considered, including atmospheric flow variables, structural variables, and inertial (lumped mass) variables. UQ results are explored for a range of output metrics (with a focus on dynamic flutter stability), for both subsonic and transonic Mach numbers, for two different CFD mesh refinements. A particular focus is placed on computing failure probabilities: the probability that the wing will flutter within the flight envelope.

Stanford, Bret K.↗