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At least 397 records · Page 22

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NASA NTRSDate not supplied

Multi-point Jig Twist Optimization of Mach 0.745 Transonic Truss-Braced Wing Aircraft and High-Fidelity CFD Validation

This paper presents a multi-point jig twist optimization study of the Mach 0.745 Transonic Truss-Braced Wing (TTBW) aircraft using an in-house developed aero-structural analysis solver VSPAERO coupled to BEAM3D. A vortex-lattice model of the TTBW model is developed, and a transonic small disturbance /integral boundary layer correction method is implemented in the VSPAERO model to account for transonic and viscous flow effects. A correction method for the wing-strut interference aerodynamics is developed and applied to the VSPAERO solver. Also, a structural dynamic finite-element model of the TTBW aircraft is developed. This finite-element model includes the geometric nonlinear effect due to the tension in the struts which causes a deflection-dependent nonlinear stiffness. The VSPAERO model is coupled to the corresponding finite-element model to provide a rapid aero-structural analysis. The VSPAERO model has been validated against wind tunnel test data and FUN3D CFD simulation data. Three different flight conditions corresponding to Mach 0.745 at 40,000 ft are selected for the TTBW aircraft jig twist optimization to reduce the drag coefficients at the design and off-design cruise lift coefficients. The preliminary optimization results show that the TTBW aircraft with the optimized jig twist achieves a drag reduction of about 9 counts, 7 counts, and8 counts corresponding to the lift coefficients 0.68, 0.73, and 0.78, respectively. A high-fidelity CFD solver FUN3D is used to validate the jig twist optimization.

Multi-point↗

NASA NTRS1997

Automating the Process of Optimization in Spacecraft Design

Spacecraft design optimization is a difficult problem, due to the complexity of optimization cost surfaces, and human expertise in optimization that is necessary in order to achieve good results. In this paper, we propose the use of a set of generic, metaheuristic optimization algorithms (e.g., generic algorithms, simulated annealing), which is configured for a particular optimization problem by an adaptive problem solver based on artificial intelligence and machine learning techniques. We describe work in progress on OASIS, a system for adaptive problem solving based on these principles.

optimization↗

NASA NTRSDate not supplied

Wind-Optimal Cruise Airspeed for a Multirotor Aircraft in Urban Air Mobility

This paper first investigates the effect of wind on the wind-optimal (minimum-energy) cruise airspeed for a NASA-proposed conceptual multirotor aircraft for the urban air mobility environment. Next, energy consumption and flight duration results are compared for flying at the wind-optimal airspeed and best-range airspeed on a great-circle cruise segment under different wind conditions. Finally, the difference in energy consumption when flying to meet the assigned required time of arrival based on actual wind conditions vs. predicted wind conditions are examined and compared for the two airspeed modes (wind-optimal and best-range) for different values of wind magnitude uncertainty. The results show operational benefits of flying at the wind-optimal cruise airspeed compared to the best-range airspeed, especially understrong headwind conditions from both an energy consumption and flight duration perspective.The results also show that flying at wind-optimal airspeed under wind magnitude uncertainty has lower variability and higher predictability of energy consumption than flying at best-range airspeed.

Urban Air Mobility↗

NASA NTRS2022

Low-Earth Orbit Trajectory Optimization in the Presence of Atmospheric Uncertainty

The previous 20 to 25 years have seen a tremendous increase in space exploration, and with that an increase in the level of logistics planning needed to ensure mission success. For spacecraft that are designed to be periodically re-supplied, a key logistics consumable is propellant, as it constitutes the greatest up-mass on re-supply vehicles. A trajectory design strategy is therefore desired that minimizes propellant usage in order to ease the demand for propellant re-supply missions. This thesis develops such a strategy in three stages, and uses the International Space Station (ISS) as its testbed, as no other LEO spacecraft is more challenging from a space logistics standpoint. First, the ISS trajectory planning problem is formulated as a constrained burn optimization problem assuming a deterministic atmosphere. The cost function is total ∆v, with constraints imposed on longitude of ascending viii node (LAN) and semi-major axis (SMA) altitude. Analytic derivatives are constructed for both the cost and constraints, which are necessary given the 6-week to 2-year time frames being considered. A gradient-based optimizer is then utilized to find locally-optimal solutions to real-world ISS trajectory planning problems. Second, atmospheric uncertainty is addressed by constructing a probabilistic model of space weather data using Gaussian Processes (GPs). Bayesian inference is performed using the GP model to generate mean and covariance estimates for space weather predictions, whose pedigree is assessed against test data. The predictions are then mapped into atmospheric density via the analytic Jacchia-Roberts density model, and the effect of space weather uncertainty on orbital lifetime is examined. Third, an ISS burn execution uncertainty model is developed. This model, along with the space weather uncertainty model, are deployed in a linear covariance analysis to ascertain their combined effect on LAN and SMA altitude dispersions. The deterministic constraints from the original problem are re-formulated as stochastic constraints, where now the constraint uncertainty interval is required to fall within specified bounds. An updated optimization framework is constructed using the original ∆v cost function along with the stochastic constraints to solve the trajectory optimization problem under atmospheric uncertainty. Finally, the complete architecture is summarized for deployment in an operational setting.

Trajectory Optimization↗

NASA NTRSDate not supplied

Aeroelastic Trim Drag Optimization of Mach 0.8 Transonic Truss-Braced Wing Aircraft using High-Lift Devices and Control Surfaces

This paper presents an aeroelastic trim drag optimization study of the Mach 0.8 Transonic Truss-Braced Wing (TTBW) aircraft using the High-lift devices and control surfaces. An aero-structural analysis solver VSPAERO with transonic small disturbance, integral boundary-layer, and wing-strut interference corrections coupled to mode shapes computed by NASTRAN using the Galerkin method is developed to provide a rapid aircraft aeroelastic performance evaluation. Three different flight conditions corresponding to Mach 0.8 are selected for the aeroelastic trim drag optimization at the design and off-design cruise lift coefficients. The preliminary optimization results show that the TTBW aircraft with the optimized deflection of the high-lift devices and control surfaces achieves a drag reduction of about 8.2 counts, 6.5 counts, and 9.7 counts corresponding to the lift coefficients 0.661, 0.695, and 0.729, respectively. A high-fidelity CFD solver FUN3D is used to verify the aeroelastic trim drag optimization.

TTBW↗

NASA NTRSDate not supplied

Implementation of Combinatorial Optimization Techniques for Automated Fiber Placement Through Thickness Defect Stack-Up Minimization

The Computer Aided Process Planning (CAPP) module was developed to facilitate and accelerate the process planning workflow for Automated Fiber Placement (AFP). CAPP assists process planners in identifying optimal starting point locations and layup strategies for each ply of a laminate. Ply optimization operates on measurement and scoring of geometry-based defects such as gaps, overlaps, angle deviation, and steering. This paper expands on the established framework for analyzing defect stack-up through thickness of a laminate. Four different combinatorial optimization algorithms are implemented and evaluated: (1) genetic algorithm, (2) differential evolution, (3) particle swarm, and (4) greedy search. The algorithms identify the optimal combination of ply-level layup strategies, by scoring potential laminates on defect stacking, using two different objective functions. A final optimization approach is also presented which trades some performance for a large gain in efficiency. These approaches are compared to a randomized combination using a complex tool surface in a virtual case study. The result is a streamlined methodology for comparing different laminate-level manufacturing strategies and minimizing the through thickness defect stack up.

CAPP↗

NASA NTRSDate not supplied

Towards Low-Noise Design of a Proprotor with the Vortex Lattice Method and Gradient-Based Optimization

This work aims to combine an aerodynamic model based on the unsteady vortex lattice method with an acoustic model provided by Farassat's formulation 1A to perform gradient-based optimizations of a proprotor with aerodynamic and acoustic constraints. The resulting combination of tools is applied to the problem of designing a single proprotor operating at a cruise condition, with and without an acoustic constraint and wing placed downstream of the proprotor rotation plane. Results are compared to a baseline design studied previously, and to similar optimizations performed with a simpler blade element momentum theory aerodynamic model. Each optimization case achieved feasibility and made significant improvements in the objective function, but the optimality criterion was not satisfied. Overall the designs the optimizer found roughly comported with our previous experience with similar problems, with some discrepancies that are discussed.

Aerodynamics↗

NASA NTRSDate not supplied

Towards Low-Noise Design of a Proprotor with the Vortex Lattice Method and Gradient-Based Optimization

Aerodynamics↗

NASA NTRSDate not supplied

Gradient-Based Optimization of the Common Research Model Wing Subject to CFD-Based Gust and Flutter Constraints

The linearized frequency-domain method was recently implemented in the stabilized finite element solver in NASA’s FUN3D code. Previous work by the authors used this method for enforcing flutter constraints during gradient-based optimizations. More recently, the solver was expanded to account for continuous (also known as stochastic) gust responses. This paper expands on recent Common Research Model wing optimization work, which demonstrated gradient-based optimization with flutter and stochastic gust constraints, among others. While that work utilized FUN3D for static aeroelastic solutions but relied on doublet lattice aerodynamics for gust and flutter responses, the present work replaces these unsteady aerodynamic analyses with those of FUN3D’s linearized frequency-domain solver. With analytic derivatives available, gradient-based optimization is performed through the use of the OpenMDAO/MPhys libraries with over 700 shape, structural, and aerodynamic design variables and over 10 nonlinear constraints. Comparisons of analysis results and optimized designs are made between doublet lattice and linearized frequency-domain solutions.

aeroelasticity↗

NASA NTRSDate not supplied

Aerodynamic Design Optimization for Natural Laminar Flow Airfoils

Natural laminar flow technology is a passive laminar flow control (LFC) strategy that seeks to delay the onset of boundary-layer transition (BLT) through shape optimization to reduce the drag of the aerodynamic vehicle. Adjoint-based design optimization for LFC is proposed in an integrated multidisciplinary framework, which includes the computational fluid dynamics (CFD), geometry and grid deformation, and linear stability analysis (LSA) for transition prediction. In particular, the BLT location is predicted using the dual N-factor method that is based on a linear stability theory (LST) eigenvalue problem. The dual N-factor criterion accounts for the amplification of planar Tollmien-Schlichting (TS) and stationary crossflow (CF) boundary-layer instabilities to predict the transition location in three-dimensional boundary-layer flows. The adjoint-based shape optimization procedure is based on an iteratively coupled CFD and LSA methodology to converge the transition location and flow solutions, as well as to calculate the sensitivities of the aerodynamic metrics of interest with respect to the flow and shape design parameters. The RAE 2822 airfoil at 0 and 30 degrees yaw angles, an angle of attack of 0.72 degrees, and subsonic conditions (M∞ = 0.19, Rec = 5.6 × 106 ) are used as baseline configurations for design optimization. The angle of attack and the vertical displacement of free-form-deformation control points are used as design variables to reduce the drag coefficient while reaching a specified lift coefficient. The optimized unswept airfoil designs achieve a 30% drag reduction accompanied by a downstream shift of the transition locations over both suction and pressure sides of the airfoil. The initial design iterations for the swept case also show a favorable trend in the drag reduction with transition delay over both sides.

Transition↗

NASA NTRSDate not supplied

Aviary: An Open-Source Multidisciplinary Design, Analysis, and Optimization Tool for Modeling Aircraft with Analytic Gradients

In recent years demands on aircraft design methods have begun to require higher degrees of coupling between disciplines and optimization in order to satisfy competing objectives involving large numbers of design parameters that define unconventional configurations. These expanding requirements have amplified a need for new and improved aircraft design, analysis, and optimization codes that are capable of performing coupled design and exploiting analytic gradients to perform gradient-based optimization where possible. To address this need, a new multidisciplinary design optimization and analysis tool called Aviary is presented. This tool, built on OpenMDAO, allows for tightly coupled, simultaneous aircraft and subsystem design using analytic gradients. Aviary includes methods from two NASA developed legacy aircraft analysis tools and provides native analytically differentiated calculations for five different disciplines (weights and sizing, aerodynamics, geometry, propulsion, and mission analysis), while also allowing external discipline analysis tools to be coupled, regardless of whether those tools can provide analytic gradients. Verification and preliminary examples and modeling efforts show Aviary’s ability to effectively model novel concepts and explore large and non-intuitive design spaces. Additionally, a multi-level user interface in Aviary creates an easy entry point for users with any level of multidisciplinary design, analysis, and optimization experience.

optimization↗

NASA NTRS1972

An Optimization study on a hybrid computer

The maximum principle is applied to minimum-time optimal-control problems, and an optimization algorithm is presented which can be implemented on a hybrid computer. The state and adjoint equations are set up on ASTRAC 2, a high-speed analog computer capable of 1000 differential equation solutions per second. The optimization algorithm is implemented on a PDP-9, an 18-bit, digital computer. The optimization scheme has global and local search phases and uses a vector optimization criterion. Second and third-order bang-bang control systems are studied as examples.

Gonzalez, R. S.↗

NASA NTRS1974

NBODY - a multipurpose trajectory optimization computer program

Documentation of the NBODY trajectory optimization program is presented in the form of a mathematical development plus a user's manual. Optimal multistage-launch ascent trajectories may be determined by variational thrust steering during the upper phase. Optimal low-thrust interplanetary spacecraft trajectories may also be calculated with solar power or constant power, all-propulsion or embedded coast arcs, fixed or optimal thrust angles, and a variety of terminal end conditions. A hybrid iteration scheme solves the boundary-value problem, while either transversality conditions or a univariate search scheme optimize vehicle or trajectory parameters.

Strack, W. C.↗

NASA NTRS1974

A comparison of two types of structural optimization procedures for satisfying flutter requirements

A comparison is made of results obtained from mathematical programming and optimality criteria procedures for the minimum-mass design of typical aircraft wing structures to satisfy prescribed flutter requirements. The mathematical programming method is based on an interior penalty function approach. A rigorous optimality criterion and an intuitive optimality criterion based on uniform strain energy density are considered. An intuitive resizing procedure is used for both optimality criterion solutions. All results are calculated using the same computer program, changing only the optimization procedure. Both high- and low-aspect-ratio wings are examined. Finite elements are used for structural modeling, and the generalized coordinates for the flutter solution are based on the natural vibration modes of the structure.

Haftka, R. T.↗

NASA NTRS1975

Optimization of structures undergoing harmonic or stochastic excitation

The optimal design was investigated of simple structures subjected to dynamic loads, with constraints on the structures' responses. Optimal designs were examined for one dimensional structures excited by harmonically oscillating loads, similar structures excited by white noise, and a wing in the presence of continuous atmospheric turbulence. The first has constraints on the maximum allowable stress while the last two place bounds on the probability of failure of the structure. Approximations were made to replace the time parameter with a frequency parameter. For the first problem, this involved the steady state response, and in the remaining cases, power spectral techniques were employed to find the root mean square values of the responses. Optimal solutions were found by using computer algorithms which combined finite elements methods with optimization techniques based on mathematical programming. It was found that the inertial loads for these dynamic problems result in optimal structures that are radically different from those obtained for structures loaded statically by forces of comparable magnitude.

Johnson, E. H.↗

NASA NTRS1975

Robustly optimal rate one-half binary convolutional codes

Three optimality criteria for convolutional codes are considered in this correspondence: namely, free distance, minimum distance, and distance profile. Here we report the results of computer searches for rate one-half binary convolutional codes that are 'robustly optimal' in the sense of being optimal for one criterion and optimal or near-optimal for the other two criteria. Comparisons with previously known codes are made. The results of a computer simulation are reported to show the importance of the distance profile to computational performance with sequential decoding.

Johannesson, R.↗

NASA NTRS1976

Optimal periodic proof test based on cost-effective and reliability criteria

An exploratory study for the optimization of periodic proof tests for fatigue-critical structures is presented. The optimal proof load level and the optimal number of periodic proof tests are determined by minimizing the total expected (statistical average) cost, while the constraint on the allowable level of structural reliability is satisfied. The total expected cost consists of the expected cost of proof tests, the expected cost of structures destroyed by proof tests, and the expected cost of structural failure in service. It is demonstrated by numerical examples that significant cost saving and reliability improvement for fatigue-critical structures can be achieved by the application of the optimal periodic proof test. The present study is relevant to the establishment of optimal maintenance procedures for fatigue-critical structures.

Yang, J.-N.↗

NASA NTRS1976

Optimization of continuous one-dimensional structures under steady harmonic excitation

The paper examines some questions relating to the optimal design of continuous one-dimensional structures driven by harmonically oscillating loads. Optimal-control methods are applied to a cantilever bar driven sinusoidally by an axial force at its tip to illustrate the minimum-weight design of one-dimensional structures under dynamic excitation. Realistic constraints are imposed during the optimizations, including a maximum allowable stress amplitude at any point along the bar and a minimum cross-sectional area. It is shown that in the absence of damping, the design space may contain many disjoint feasible regions, and multiple optima can exist. Detailed solutions are obtained for continuous bars with an excitation frequency less than, and then greater than, the fundamental free-vibration frequency. It is found that above a certain excitation frequency, two or more arcs with different constraints characterize the optimal designs. It is concluded that when more than two different constrained arcs characterize the optimal solution, the continuum approach may be impractical, and finite-element approximations may offer the only alternative.

Johnson, E. H.↗