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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
NASA NTRS2012

Computational Optimization of a Natural Laminar Flow Experimental Wing Glove

Computational optimization of a natural laminar flow experimental wing glove that is mounted on a business jet is presented and discussed. The process of designing a laminar flow wing glove starts with creating a two-dimensional optimized airfoil and then lofting it into a three-dimensional wing glove section. The airfoil design process does not consider the three dimensional flow effects such as cross flow due wing sweep as well as engine and body interference. Therefore, once an initial glove geometry is created from the airfoil, the three dimensional wing glove has to be optimized to ensure that the desired extent of laminar flow is maintained over the entire glove. TRANAIR, a non-linear full potential solver with a coupled boundary layer code was used as the main tool in the design and optimization process of the three-dimensional glove shape. The optimization process uses the Class-Shape-Transformation method to perturb the geometry with geometric constraints that allow for a 2-in clearance from the main wing. The three-dimensional glove shape was optimized with the objective of having a spanwise uniform pressure distribution that matches the optimized two-dimensional pressure distribution as closely as possible. Results show that with the appropriate inputs, the optimizer is able to match the two dimensional pressure distributions practically across the entire span of the wing glove. This allows for the experiment to have a much higher probability of having a large extent of natural laminar flow in flight.

Hartshom, Fletcher↗
NASA NTRS1988

A study of the use of linear programming techniques to improve the performance in design optimization problems

This project has two objectives. The first is to determine whether linear programming techniques can improve performance when handling design optimization problems with a large number of design variables and constraints relative to the feasible directions algorithm. The second purpose is to determine whether using the Kreisselmeier-Steinhauser (KS) function to replace the constraints with one constraint will reduce the cost of total optimization. Comparisons are made using solutions obtained with linear and non-linear methods. The results indicate that there is no cost saving using the linear method or in using the KS function to replace constraints.

Young, Katherine C.↗
NASA NTRS2013

Adaptive Control for Linear Uncertain Systems with Unmodeled Dynamics Revisited via Optimal Control Modification

This paper presents the optimal control modification for linear uncertain plants. The Lyapunov analysis shows that the modification parameter has a limiting value depending on the nature of the uncertainty. The optimal control modification exhibits a linear asymptotic property that enables it to be analyzed in a linear time invariant framework for linear uncertain plants. The linear asymptotic property shows that the closed-loop plants in the limit possess a scaled input-output mapping. Using this property, we can derive an analytical closed-loop transfer function in the limit as the adaptive gain tends to infinity. The paper revisits the Rohrs counterexample problem that illustrates the nature of non-robustness of model-reference adaptive control in the presence of unmodeled dynamics. An analytical approach is developed to compute exactly the modification parameter for the optimal control modification that stabilizes the plant in the Rohrs counterexample. The linear asymptotic property is also used to address output feedback adaptive control for non-minimum phase plants with a relative degree 1.

Unmodeled Dynamics↗
NASA NTRS2011

Engine Yaw Augmentation for Hybrid-Wing-Body Aircraft via Optimal Control Allocation Techniques

Asymmetric engine thrust was implemented in a hybrid-wing-body non-linear simulation to reduce the amount of aerodynamic surface deflection required for yaw stability and control. Hybrid-wing-body aircraft are especially susceptible to yaw surface deflection due to their decreased bare airframe yaw stability resulting from the lack of a large vertical tail aft of the center of gravity. Reduced surface deflection, especially for trim during cruise flight, could reduce the fuel consumption of future aircraft. Designed as an add-on, optimal control allocation techniques were used to create a control law that tracks total thrust and yaw moment commands with an emphasis on not degrading the baseline system. Implementation of engine yaw augmentation is shown and feasibility is demonstrated in simulation with a potential drag reduction of 2 to 4 percent. Future flight tests are planned to demonstrate feasibility in a flight environment.

Taylor, Brian R.↗
NASA NTRS2011

Engine Yaw Augmentation for Hybrid-Wing-Body Aircraft via Optimal Control Allocation Techniques

Asymmetric engine thrust was implemented in a hybrid-wing-body non-linear simulation to reduce the amount of aerodynamic surface deflection required for yaw stability and control. Hybrid-wing-body aircraft are especially susceptible to yaw surface deflection due to their decreased bare airframe yaw stability resulting from the lack of a large vertical tail aft of the center of gravity. Reduced surface deflection, especially for trim during cruise flight, could reduce the fuel consumption of future aircraft. Designed as an add-on, optimal control allocation techniques were used to create a control law that tracks total thrust and yaw moment commands with an emphasis on not degrading the baseline system. Implementation of engine yaw augmentation is shown and feasibility is demonstrated in simulation with a potential drag reduction of 2 to 4 percent. Future flight tests are planned to demonstrate feasibility in a flight environment.

Taylor, Brian R.↗
NASA NTRS2001

A Closed-Loop Optimal Neural-Network Controller to Optimize Rotorcraft Aeromechanical Behaviour: Output from Two Sample Cases - Volume 2

A closed-loop optimal neural-network controller technique was developed to optimize rotorcraft aeromechanical behaviour. This technique utilities a neural-network scheme to provide a general non-linear model of the rotorcraft. A modem constrained optimisation method is used to determine and update the constants in the neural-network plant model as well as to determine the optimal control vector. Current data is read, weighted, and added to a sliding data window. When the specified maximum number of data sets allowed in the data window is exceeded, the oldest data set is and the remaining data sets are re-weighted. This procedure provides at least four additional degrees-of-freedom in addition to the size and geometry of the neural-network itself with which to optimize the overall operation of the controller. These additional degrees-of-freedom are: 1. the maximum length of the sliding data window, 2. the frequency of neural-network updates, 3. the weighting of the individual data sets within the sliding window, and 4. the maximum number of optimisation iterations used for the neural-network updates.

Leyland, Jane Anne↗
NASA NTRS1987

Simultaneous structure/control optimization of large flexible spacecraft

This paper presents an approach to the simultaneous optimal design of a structure and control system for large flexible spacecrafts based on realistic objective function and constraints. The weight or total cost of structure and control system is minimized subject to constraints on the magnitude of response to a given disturbance involving both rigid-body and elastic modes. A nested optimization technique is developed to solve the combined problem. As an example, simple beam-like spacecraft under a steady-state white-noise disturbance force is investigated and some results of optimization are presented. In the numerical examples, the stiffness distribution, the location of controller and the control gains are optimized. Direct feedback control and linear quadratic optimal control laws are used with both inertial and non-inertial disturbing force. It is shown that the total cost is sensitive to the overall structural stiffness so that a simultaneous optimization of the structure and control system is indeed useful.

Onoda, Junjiro↗
NASA NTRS2019

Optimization of Lyot Coronagrah focal plane masks for improved low-order wavefront sensing

The WFIRST Coronagraph uses a Low-Order Wavefront Sensing and Control (LOWFS/C) subsystem to stabilize the stellar wavefront. This is true for the Hybrid Lyot Coronagraph (HLC), the Shaped Pupil Coronagraph (SPC) spectrograph, and the SPC wide field of view modes. For the SPC spectrograph, we have found via modeling and simulations that a focal plane mask (FPM) with an elliptical phase dimple can reduce the LOWFS errors significantly compared to the conventional, circular phase dimple. For HLC designs, we concurrently optimized the FPM parameters and deformable mirror shapes using our open-source software toolbox, the Fast Linearized Coronagraph Optimizer (FALCO). This process resulted in new FPMs with non-uniform central-area phase modulation. We have found in numerical simulations that such FPMs still provide sufficient LOWFS performance. In this paper, we will present the LOWFS performance for several new HLC and SPC FPM designs.

Riggs, A.J. Eldorado↗
NASA NTRS1983

Dynamics and control of forward swept wing aircraft

Aspects of non-zero differential game theory with application to multivariable control synthesis and optimal linear control law design using optimum parameter sensitivity analysis are discussed.

Schmidt, D. K.↗
NASA NTRS2003

Matrix Cracking in Four Different 2D SiC/SiC Composite Systems

Silicon carbide fiber reinforced, silicon carbide matrix composites are some of the most advanced composite systems for high-temperature, high-stress applications in oxidizing environments. A basic area that needs to be understood for the purpose of material behavior modeling and optimization is the architectural, constituent, and mechanistic factors that contribute to non-linear stress-strain behavior. The mechanism that causes non-linear stress-strain in dense-matrix composites is the formation and propagation of bridged matrix cracks. In addition, the occurrence and propagation of matrix cracks controls the time-dependent strength-properties of these materials in oxidizing environments at elevated temperatures. A modal acoustic emission technique has been used to monitor and estimate the stress-dependent matrix cracking. Two different SiC matrix systems, chemical vapor infiltrated (CVI) and melt-infiltrated (MI), with two different SiC fiber reinforcement, Hi-Nicalon (trademark) and Sylramic (trademark) were compared. Even though the averages of the range where matrix cracking occurred for the composites varied by more than 0.1% in strain and almost 200 MPa in stress, the range or distribution for matrix cracking could be reduced to a narrow band of stress for CVI SiC and MI SiC composites if it were assumed that all matrix cracks emanate outside of the load-bearing fiber, interphase, CVI preform minicomposite. A simple relationship was determined to describe stress-dependent matrix cracking which can then be used to estimate the onset of large, bridged matrix cracks or for material behavior models.

Morscher, Gregory N.↗
NASA NTRSDate not supplied

Method for Extracting Aerodynamic Coefficients and Winds On-the-Fly Using Real-Time GPS Data

The landing accuracy of an autonomous guided parafoil is influenced by its ability to predict the trajectory, which is shaped by the parafoil’s aerodynamic characteristics and atmospheric winds. The parafoil is subjective to imperfections from manufacturing, damage during deployment, lateral asymmetry, and so forth, leading to discrepancies between the actual aerodynamic properties and the onboard aerodynamic model. Thus, by acquiring an accurate knowledge of the aerodynamic properties and real-time winds, the onboard simulation can reduce the undertainties in the dynamics modeling for trajectory propagation to improve the landing accuracy. For that purpose, a non-linear least-squares method is developed to calculate differential corrections for optimizing and extracting the parafoil aerodynamic coefficients and winds on-the-fly using real-time data from the Global Positioning System (GPS). Post-flight analyses from two test flights have shown that the method provides improved simulations that closely match the GPS trajectories.

Lisa Ling↗
NASA NTRS1992

Non-linear dynamic compensation system

A non-linear dynamic compensation subsystem is added in the feedback loop of a high precision optical mirror positioning control system to smoothly alter the control system response bandwidth from a relatively wide response bandwidth optimized for speed of control system response to a bandwidth sufficiently narrow to reduce position errors resulting from the quantization noise inherent in the inductosyn used to measure mirror position. The non-linear dynamic compensation system includes a limiter for limiting the error signal within preselected limits, a compensator for modifying the limiter output to achieve the reduced bandwidth response, and an adder for combining the modified error signal with the difference between the limited and unlimited error signals. The adder output is applied to control system motor so that the system response is optimized for accuracy when the error signal is within the preselected limits, optimized for speed of response when the error signal is substantially beyond the preselected limits and smoothly varied therebetween as the error signal approaches the preselected limits.

Lin, Yu-Hwan↗
NASA NTRS2003

Genetic Algorithm Tuned Fuzzy Logic for Gliding Return Trajectories

The problem of designing and flying a trajectory for successful recovery of a reusable launch vehicle is tackled using fuzzy logic control with genetic algorithm optimization. The plant is approximated by a simplified three degree of freedom non-linear model. A baseline trajectory design and guidance algorithm consisting of several Mamdani type fuzzy controllers is tuned using a simple genetic algorithm. Preliminary results show that the performance of the overall system is shown to improve with genetic algorithm tuning.

Burchett, Bradley T.↗
NASA NTRS1973

Synthesis of a non-linear feedback system with significant plant-ignorance for prescribed time-domain tolerances

The problem considered is the design of a feedback system containing a linear, time invariant, minimum phase plant, whose parameters are known only within given bounds, such that the time response of the system remains within specified limits. A quasi-optimal design, for given design constraints, is one which minimizes the effect of white sensor noise on the input to the plant. An investigation was conducted on the use of the non linear device known as the Clegg integrator in the design of such a system. The describing function of the Clegg integrator has the same magnitude characteristic, apart from a scale factor, as the linear integrator, but has 52 deg less phase-lag, at all frequencies, than the linear integrator; thus, when used in a feedback system, it provides a larger stability margin than the linear integrator. This property allows the nonlinear feedback system to be designed so that the sensor noise is attenuated more than in the linear design.

Krishnan, K. R.↗
NASA NTRS2015

An Expert System-Driven Method for Parametric Trajectory Optimization During Conceptual Design

During the early phases of engineering design, the costs committed are high, costs incurred are low, and the design freedom is high. It is well documented that decisions made in these early design phases drive the entire design's life cycle cost. In a traditional paradigm, key design decisions are made when little is known about the design. As the design matures, design changes become more difficult in both cost and schedule to enact. The current capability-based paradigm, which has emerged because of the constrained economic environment, calls for the infusion of knowledge usually acquired during later design phases into earlier design phases, i.e. bringing knowledge acquired during preliminary and detailed design into pre-conceptual and conceptual design. An area of critical importance to launch vehicle design is the optimization of its ascent trajectory, as the optimal trajectory will be able to take full advantage of the launch vehicle's capability to deliver a maximum amount of payload into orbit. Hence, the optimal ascent trajectory plays an important role in the vehicle's affordability posture yet little of the information required to successfully optimize a trajectory is known early in the design phase. Thus, the current paradigm of optimizing ascent trajectories involves generating point solutions for every change in a vehicle's design parameters. This is often a very tedious, manual, and time-consuming task for the analysts. Moreover, the trajectory design space is highly non-linear and multi-modal due to the interaction of various constraints. When these obstacles are coupled with the Program to Optimize Simulated Trajectories (POST), an industry standard program to optimize ascent trajectories that is difficult to use, expert trajectory analysts are required to effectively optimize a vehicle's ascent trajectory. Over the course of this paper, the authors discuss a methodology developed at NASA Marshall's Advanced Concepts Office to address these issues. The methodology is two-fold: first, capture the heuristics developed by human analysts over their many years of experience; and secondly, leverage the power of modern computing to evaluate multiple trajectories simultaneously and therefore enable the exploration of the trajectory's design space early during the pre- conceptual and conceptual phases of design. This methodology is coupled with design of experiments in order to train surrogate models, which enables trajectory design space visualization and parametric optimal ascent trajectory information to be available when early design decisions are being made.

Dees, Patrick D.↗
NASA NTRS2025

Mission-Maps For Outbound Cislunar Transfer Trajectories

This study quantifies the robustness and sensitivity of an outbound cislunar trajectory for a lunar lander in the form of mission-maps, or topological maps that allows either a computer program or mission designer to intuitively optimize the placement of critical outbound correction burns from the derived sensitivity data. The non-linear multi-body dynamics are applied to generate an outbound cislunar reference profile used by a linear covariance analysis (LinCov) tool to compute the expected Δv and trajectory dispersions due to the initial state uncertainty, sensor errors, maneuver execution errors, and disturbance accelerations along the outbound cislunar profile. The rapid performance analysis capabilities of LinCov are complimented with parallel processing techniques to evaluate hundreds and thousands of different translational burn locations, placements, and targeting constraints to identify the combination that minimizes the total Δv usage (nominal plus 3σ Δv) and trajectory dispersions at lunar orbit insertion. This study utilizes a generalized reference targeting algorithm to quickly assess the integrated closed-loop GN&C system performance due to different targeting configurations and constraints. The resulting mission maps provide an intuitive insight to ascertain each trajectory correction maneuver’s (TCM) sensitivity to different burn times along an outbound cislunar trajectory and quickly identify desirable engineering tradeoffs when performing analysis on the number and placement of these burns that nominally zero. Multiple mission maps are generated for a variety of different performance parameters that allow engineers to visually identify optimal solutions for trajectory correction maneuver placements, the number of correction burns, and the targeting constraints for each burn.

GN&C↗
NASA NTRS1996

A Review of High-Order and Optimized Finite-Difference Methods for Simulating Linear Wave Phenomena

This paper presents a review of high-order and optimized finite-difference methods for numerically simulating the propagation and scattering of linear waves, such as electromagnetic, acoustic, or elastic waves. The spatial operators reviewed include compact schemes, non-compact schemes, schemes on staggered grids, and schemes which are optimized to produce specific characteristics. The time-marching methods discussed include Runge-Kutta methods, Adams-Bashforth methods, and the leapfrog method. In addition, the following fourth-order fully-discrete finite-difference methods are considered: a one-step implicit scheme with a three-point spatial stencil, a one-step explicit scheme with a five-point spatial stencil, and a two-step explicit scheme with a five-point spatial stencil. For each method studied, the number of grid points per wavelength required for accurate simulation of wave propagation over large distances is presented. Recommendations are made with respect to the suitability of the methods for specific problems and practical aspects of their use, such as appropriate Courant numbers and grid densities. Avenues for future research are suggested.

Zingg, David W.↗