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NASA NTRS2017

Coronagraph Design Optimization for Segmented Aperture Telescopes

The goal of directly imaging Earth-like planets in the habitable zone of other stars has motivated the design of coronagraphs for use with large segmented aperture space telescopes. In order to achieve an optimal trade-o between planet light throughput and di racted starlight suppression, we consider coronagraphs comprised of a stage of phase control implemented with deformable mirrors (or other optical elements), pupil plane apodization masks (gray scale or complex valued), and focal plane masks (either amplitude only or complex-valued, including phase only such as the vector vortex coronagraph). The optimization of these optical elements, with the goal of achieving 10 or more orders of magnitude in the suppression of on-axis (starlight) di racted light, represents a challenging non-convex optimization problem with a nonlinear dependence on control degrees of freedom. We develop a new algorithmic approach to the design optimization problem, which we call the "Auxiliary Field Optimization" (AFO) algorithm. The central idea of the algorithm is to embed the original optimization problem, for either phase or amplitude (apodization) in various planes of the coronagraph, into a problem containing additional degrees of freedom, speci cally ctitious "auxiliary" electric elds which serve as targets to inform the variation of our phase or amplitude parameters leading to good feasible designs. We present the algorithm, discuss details of its numerical implementation, and prove convergence to local minima of the objective function (here taken to be the intensity of the on-axis source in a "dark hole" region in the science focal plane). Finally, we present results showing application of the algorithm to both unobscured o -axis and obscured on-axis segmented telescope aperture designs. The application of the AFO algorithm to the coronagraph design problem has produced solutions which are capable of directly imaging planets in the habitable zone, provided end-to-end telescope system stability requirements can be met. Ongoing work includes advances of the AFO algorithm reported here to design in additional robustness to a resolved star, and other phase or amplitude aberrations to be encountered in a real segmented aperture space telescope.

Redding, Dave↗

NASA NTRS2018

An Active Subspace Method for Accelerating Convergence in Delaunay-Based Optimization via Dimension Reduction

Delaunay-based derivative-free optimization, ∆DOGS, is an efﬁcient and provably-convergent global optimization method for the problems which has computationally expensive objection function and the analytical expression for the objective function is not available. ∆-DOGS is a novel optimization scheme in the family of response surface methods (RSMs); however, it suffers from the curse of dimensionality since the computational cost increases dramatically as the number of design parameters increases. As a result, the number of design parameters in ∆-DOGS algorithm is relatively low (n.10). To avoid such problems, this paper proposes a combination of derivative-free optimization, seeking the global minimizer of an expensive and nonconvex objective function f(x) and active subspace method, detecting the directions of the most variability using evaluations of the gradient. The contribution of other directions to the objective function is bounded by a sufﬁciently small constant. This new algorithm iteratively applied Delaunay-based derivative-free optimization to seek the minimizer on the d-dimensional active subspace that has most function variation. Inverse mapping is needed to project data from active subspace to full-model for evaluating function values. This task is overcome by solving an inequality constrained problem that curves the response surface of the objective function. The test results show that this strategy is effective on a handful of optimization problems.

Bewley, Thomas R.↗

NASA NTRSDate not supplied

Optimizing Proprotor Blades Using Coupled Aeroacoustic and Aerodynamic Sensitivities

A quieter and aerodynamically more efficient proprotor design requires high-fidelity and well-integrated optimization and analysis tools. To fulfill that requirement, the present paper delivers a methodology based on multidisciplinary, adjoint-based, discrete optimization. SU2-based code development involves the implementation of aeroacoustic analysis, adjoint computations, and integrations into a multidisciplinary rotorcraft optimization suite. Submodules utilized in the optimization are verified with wind tunnel data to demonstrate the accuracy of aerodynamic and aeroacoustic analyses. The developed code is used for NASA's helically twisted proprotor to maximize the aeroacoustic performance of the proprotor while holding thrust constant. The optimization process considers multiple flight conditions (hence, multipoint), which are forward flight and hovering. As an outcome of the analyses, the optimized blade design propagates lower noise as perceived by multiple observers in both flight conditions

R Omur Icke↗

NASA NTRSDate not supplied

Aeroelastic Trim Drag Optimization of Mach 0.745 Transonic Truss-Braced Wing Aircraft with Variable-Camber Continuous Trailing-Edge Flap

This paper presents an aeroelastic trim drag optimization study of the Mach 0.745 Transonic Truss-Braced Wing (TTBW) aircraft with the Variable-Camber Continuous Trailing-Edge Flap (VCCTEF). An aero-structural analysis solver VSPAERO with transonic small disturbance, integral boundary-layer, and wing-strut interference corrections coupled to finite-element code BEAM3D is developed to provide a rapid aircraft aeroelastic performance evaluation. The VSPAERO model has been validated against wind tunnel test data. Aeroelastic trim drag optimization studies are conducted for a VCCTEF configuration with 6-spanwise sections. Three different flight conditions corresponding to Mach 0.745 are selected for the TTBW aircraft 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 VCCTEF deflection achieves a drag reduction of about 9.1 counts, 5.9 counts, and 11.8 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 aeroelastic trim drag optimization.

Aeroelastic trim drag↗

NASA NTRSDate not supplied

Flutter-Constrained Optimization with the Linearized Frequency-Domain Approach

Due to the high computational cost associated with unsteady aeroelastic analysis, state-of-the-art aeroelastic optimizations based on computational fluid dynamics typically ignore critical constraints like flutter and aeroelastic gust response. The linearized frequency-domain method offers an approach for adding high-fidelity flutter constraints to multidisciplinary optimizations at relatively low cost compared to other unsteady computational fluid dynamics methods. In recent work, sensitivities have been implemented for the linearized frequency-domain method in FUN3D. In this work, the linearized frequency-domain method and associated sensitivities are applied to gradient-based aeroelastic optimization with flutter constraints based on computational fluid dynamics. An overview of the flutter constraint formulation and implementation is provided, and then two optimization problems are presented. The first optimization increases the flutter speed of a pitch and plunge airfoil at transonic conditions using the minimal amount of geometric changes. The second optimization minimizes the mass of the AGARD 445.6 wing subject to a flutter constraint.

Aeroelasticity↗

NASA NTRSDate not supplied

Flutter-Constrained Optimization with the Linearized Frequency-Domain Approach

Aeroelasticity↗

NASA NTRSDate not supplied

Investigation of a Smooth Local Correlation-based Transition Model in a Discrete-Adjoint Aerodynamic Shape Optimization Algorithm

A smooth local correlation-based transition model is fully coupled to a RANS-based Newton-Krylov flow solver and discrete-adjoint gradient-based optimization algorithm. The free-transition optimization framework is evaluated using lift-constrained drag minimizations of airfoils at design conditions ranging from light to single-aisle aircraft and an infinite swept wing at design conditions representative of a transonic strut-braced wing aircraft. The impact of the streamwise grid resolution on the ability of the optimization algorithm to delay boundary-layer transition is investigated, with the results demonstrating that streamwise grid resolution requirements increase as the transition length decreases with increasing Reynolds number. The optimization problem at the light aircraft design conditions is demonstrated to be multi-modal, with the optimization algorithm producing two distinct designs: one with a thin, reflexed trailing edge and steep pressure recovery regions, the other with increased aft loading, with the latter design outperforming the former. A drag minimization of an airfoil at transonic design conditions demonstrates that the optimization algorithm successfully trades a decrease in viscous drag by delaying boundary-layer transition with an increase in wave drag, while the drag minimization of an infinite swept wing demonstrates the capability of the optimizational gorithm to delay both Tollmien-Schlichting and stationary crossflow instabilities.

AATT↗

NASA NTRSDate not supplied

Aeroelastic Trim Drag Optimization of Mach 0.8 TransonicTruss-Braced Wing Aircraft with Variable Camber ContinuousTrailing Edge Flap

This paper presents an aeroelastic trim drag optimization study of the Mach 0.8 Tran-sonic Truss-Braced Wing (TTBW) aircraft with the Variable Camber Continuous TrailingEdge Flap (VCCTEF). An aero-structural analysis solver VSPAERO with transonic small dis-turbance, integral boundary-layer, and wing-strut interference corrections coupled to modeshapes computed by NASTRAN using the Galerkin method is developed to provide a rapidaircraft aeroelastic performance evaluation. Aeroelastic trim drag optimization studies areconducted for a VCCTEF configuration with 6-spanwise sections. Three different flight condi-tions corresponding to Mach 0.8 are selected for the aeroelastic trim drag optimization at thedesign and off-design cruise lift coefficients. The preliminary optimization results show thatthe TTBW aircraft with the optimized VCCTEF deflection achieves a drag reduction of about 9.2 counts, 9.6 counts, and 12.3 counts corresponding to the lift coefficients 0.661, 0.695, and0.729, respectively. When accounting for the actuator weight penalty, the corresponding dragreductions are 1.77%, 1.82%, 2.41%. A high-fidelity CFD solver FUN3D is used to validatethe aeroelastic trim drag optimization.

Aeroelastic trim drag↗

NASA NTRSDate not supplied

Robust Trajectory Optimization for Guided Powered Descent and Landing

A robust trajectory optimization approach for guidance algorithm gain selection for powered descent and landing is developed. This approach uses a genetic algorithm to determine optimal guidance algorithm parameters while incorporating uncertainty information from linear covariance analysis. The optimal guidance algorithm parameters are determined while accounting for environment, navigation, and vehicle property uncertainty and sensor suite fidelity. As a demonstration of this method, the optimal gains for the fractional polynomial powered descent guidance are found for the braking phase of a robotic lunar landing mission. Scenarios with differing sensor suites and sensor qualities are considered, with objective functions to minimize variability in propellant usage or terminal position. Results show that the optimal guidance algorithm gains for a given trajectory differ based on the sensor suite, and optimal guidance algorithm gains may result in up to 20% performance improvements over the baseline in propellant usage and landed accuracy.

Grace E Calkins↗

NASA NTRSDate not supplied

Robust Trajectory Optimization and GN&C Performance Analysis for NRHO Rendezvous

This paper evaluates several candidate Near-Rectilinear Halo Orbits (NRHO) rendezvous trajectory designs using linear covariance (LinCov) analysis and determines the optimal locations for NRHO rendezvous translational maneuver locations. The performance of several candidate relative trajectory designs are determined as a function of relative navigation accuracy (angles only), inertial optical navigation (OpNav), range observability maneuvers, maneuver execution errors, relative maneuver targeting, and environment uncertainties. Further, the optimal locations of rendezvous maneuvers are determined for each of the candidate reference trajectories. The long-term goal of this research is to utilize LinCov and a genetic optimization algorithm (GA) to determine a complete end-to-end optimal NRHO trajectory design that is robust to navigation errors, maneuver execution errors, and environment uncertainties. This paper represents a first step toward this goal. Three candidate rendezvous trajectories with varying numbers of range-observability maneuvers are evaluated for their robustness to uncertainties, errors, and total trajectory correction delta-v performance. Some key elements of this analysis include relative navigation performance in an NRHO, relative trajectory dispersion performance, and total 3-sigma delta-v performance. This development provides the foundation to then determine an optimal and robust end-to-end NRHO rendezvous trajectory, including the determination of the optimal locations of range observability maneuvers, if needed.

Linear Covariance Analysis↗

NASA NTRSDate not supplied

Trajectory Optimization Methods and Applications at NASA Goddard

The process of spacecraft trajectory design frequently incorporates an optimization step in which one or more objectives, such as propellant consumption or time of flight, is minimized. Optimization is especially crucial for low-thrust mission design, due to the need to specify a thrust vector at every instant in time along a trajectory. At NASA's Goddard Space Flight Center (GSFC) a number of open-source tools have been developed for spacecraft trajectory optimization that utilize direct shooting and collocation methods. These tools have been effectively applied to cislunar, libration point, and interplanetary mission design for the Lunar IceCube, SWFO, and DAVINCI missions, among others. This presentation outlines the theory underlying these optimization tools along with the details of their application to several trajectory design problems, with a focus on the Lunar IceCube (LIC) mission. The LIC mission required a low-thrust trajectory from a high-energy deployment state to a lunar orbit, and its limited control authority necessitated the use of optimization tools and low-energy trajectory design techniques. The tools discussed demonstrate how the use of optimization methods expands mission capabilities and enables transformational science.

Robert Pritchett↗

NASA NTRSDate not supplied

Optimization of Plug Nozzles Using CFD Informed Design Space Querying

This paper presents an axisymmetric CFD approach based on Reynolds-averaged Navier-Stokes (RANS) calculations for the shape optimization of plug nozzle contours for both supersonic cruise and landing/takeoff (LTO) conditions. Three key external plug design parameters were defined as independent variables in the optimization scheme, while nozzle performance was evaluated using thrust coefficient (Cfg) and discharge coefficient (Cd) as the primary dependent variables. By varying these parameters, a wide range of axisymmetric conic section plug profiles can be achieved, simplifying the problem. The paper also discusses the supersonic plug nozzle optimization approach, design space seeding, meshing, and CFD simulations for the optimization process. The results demonstrate that the approach is effective in exploring the parameter space and reducing computational expenses, making it a viable option for optimizing nozzle plug contours. Using this optimization toolchain, the study yielded preliminary designs for LTO, cruise, and LTO-cruise balanced plug nozzles.

nozzles↗

NASA NTRSDate not supplied

Optimization of Plug Nozzles Using CFD Informed Design Space Querying

CFD↗

NASA NTRSDate not supplied

Angles-Only Robust Trajectory Optimization for NRHO Rendezvous

This study demonstrates a robust trajectory optimization approach for rendezvous and proximity operations with angles-only navigation measurements. Often, sensors that directly measure relative range and velocity require communication or coordination between the chaser and target vehicle and can have limiting pointing accuracy, mass, or power requirements compared to angle measurement sensors. Thus, the capability to perform a rendezvous with only angle measurements can be advantageous for vehicle design and to improve robustness to failures. However, the well studied limitation of angles-only navigation in measuring range results in large uncertainties in the navigation system that must be reduced with chaser vehicle thrust maneuvers to induce observability in range for the navigation filter. This analysis presents a trajectory optimization problem for a lunar ascent rendezvous during a crewed lunar mission in a Near-Rectilinear Halo Orbit (NRHO) that is limited to only angle measurements. The objective of this study is to show that an angles-only rendezvous is feasible in an NRHO and to present the sensitivity to an assortment of constraints generated from a systematic optimization process using linear covariance analysis and particle swarm optimization. Linearized NRHO dynamics and linearized relative targeting are applied to use linear covariance analysis to determine the expected delta-v and trajectory dispersions due to initial state uncertainty, sensor errors, maneuver execution errors, and unmodeled dynamics. The delta-v and trajectory dispersions are passed into a particle swarm optimization algorithm to find the optimized maneuver profile that minimizes fuel use while satisfying constraints such as free drift and underburn to 3-sigma certainty. The trajectory constraints including time available, desired final uncertainty, and initial uncertainty are varied to ascertain sensitivity and desirable engineering trades.

Linear Covariance Analysis↗

NASA NTRS2024

Runtime Thread-Block Optimization for Custom Multistream CUDA Kernels for the Glenn Research Center Communication Analysis Suite

In preparation of the return of humans to the Moon with the coming Artemis missions, NASA scientists must evaluate proposed landing site locations for terrain and communications viability. The Glenn Research Center Communication Analysis Suite (GCAS) combines sophisticated communication network models with accurate lunar terrain to access sites across the Moon’s south pole. Given the importance of proper site selection to crew safety and mission success, many locations need to be analyzed resulting in a large computational load needing to be performed. To meet the growing project demands, development has begun to improve the runtime efficiency of GCAS with GPU parallelization by way of multi-stream CUDA kernels. One of the most prominent factors in kernel optimization is the proper selection of thread-block dimensions in order to maximize the concurrent operation on the device. Typically, thread-block dimensions are optimized by hand requiring many stages of benchmarking and iteration. Additionally, given the main conditions to optimization are the physical GPU architecture and problem size, these optimal dimensions are non-portable and fragile in their scope. As such, a novel optimization routine was developed to generate the optimal thread-block dimensions during runtime with considerations to hardware specifications and problem size resolving the issues of portability and enabling the function of more dynamic routines.

Aden Bergstresser↗

DOE OSTI2021

Optimization of Refrigerant Compositions for Low-GWP Refrigerant Mixtures Using Segment-by-segment Heat Exchanger and Detailed System Models

The recently introduced hydrofluoroolefin (HFO) refrigerants, including R1234yf and R1234ze(E), have significantly lower global warming potentials (GWPs) than traditional hydrofluorocarbon (HFC) refrigerants like R410A. However, prior tests show that direct drop-in of pure R1234yf or R1234ze(E) into equipment designed for R410A results in a decrease in heat exchanger capacity and the system coefficient of performance. The primary reason is the lower in-tube heat transfer performance of R1234yf and R1234ze(E) compared with that of R410A. To address this issue, previous studies have mixed the mildly flammable HFC R32 with HFOs to improve system performance, with HFC R125 also added to suppress flammability. Previous studies selected compositions based on simple cycle analyses and did not consider modifications of the heat exchanger circuitry configuration to adapt to the new refrigerants. This study presents a novel multi-objective optimization approach to design a refrigerant composition that maximizes energy efficiency within flammability and GWP limits. The approach in this work simultaneously optimizes mixture composition and heat exchanger circuitry configuration. A case study on a rooftop unit indicates that, compared with mixture-only optimization, simultaneous optimization of mixture and heat exchanger circuitry yields a 5.9% improvement in cycle efficiency and a 48.6% reduction in refrigerant flammability with a GWP of 268. Circuitry optimization using refrigerants with different temperature glides shows that the larger the temperature glide is, the larger EER improvement is obtained. The results show that zeotropic blends with a large temperature glide are more sensitive to the refrigerant circuitry than pure refrigerants and may suffer significant performance degradation with subpar heat exchanger circuitry design. The proposed optimization approach is generally applicable to mixtures with any number of components. Using this approach to design a HVAC system can yield higher system efficiency within flammability and GWP constraints.

Li, Zhenning↗

DOE OSTI2022

Optimal Wind Turbine Design for H2 Production

NREL and industrial partners GE and Nel seek to advance affordable green hydrogen production by optimizing wind turbine design specifically for hydrogen production and validating designs using NREL's ARIES facilities. This project will couple wind turbine, wind plant, solar plant, and electrolyzer models to predict hydrogen production from variable, renewable power sources. It will then use gradient-based optimization with exact-analytic gradients to optimize wind turbine rotor diameter, hub height, and power rating for optimal hydrogen production. Finally, it will validate the optimal turbine designs using the ARIES research platform, where it will compare a baseline turbine to the optimal design for a variety of scenarios and resources.

electrolyzer↗

DOE OSTI2022

Optimization control technology for building energy conservation

A simulation processor generates and stores a simulation model based on conditions associated with a physical structure, such as a building. A neural network processor implements a neural network, having an input layer coupled to receive sensor data from the structure and having an output layer coupled to supply control signals to the at least one electrically operable environmental control device. The neural network is trained using the simulation model. A particle swarm optimization processor programmed to receive the simulation results and perform particle swarm optimization, ascertains optimal parameters for controlling the at least one electrically operable environmental control device and supplies these optimal parameters to the neural network processor. The neural network processor uses the optimal parameters supplied by the particle swarm optimization processor to further train the neural network.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗