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NASA NTRS1994

Fabric geometry distortion during composites processing

Waviness and tow misalignment are often cited as possible causes of data scatter and lower compression stiffness and strength in textile composites. Strength differences of as much as 40 percent have been seen in composites that appear to have the same basic material and structural properties -- i.e., yarn orientation, yarn size, interlacing geometry. Fabric geometry distortion has been suggested as a possible reason for this discrepancy, but little quantitative data or substantial evidence exists. The focus of this research is to contribute to the present understanding of the causes and effects of geometric distortion in textile composites. The initial part of the study was an attempt to gather qualitative information on a variety of textile structures. Existing and new samples confirmed that structures with a significant direction presence would be more susceptible to distortion due to the compaction process. Thus, uniweaves (fiber vol frac: 54-72 percent) biaxial braids (vf: 34-58 percent) demonstrated very little fabric geometry distortion. In stitched panels, only slight buckling of z-direction stitches was observed, primarily near the surface. In contrast, for structures with high compaction ratios -- e.g., large cylindrical yarns (2.5:1) orpowder towpreg (4:1) -- there were visible distortions where previously smooth and periodic undulations were transformed to abrupt changes in direction. A controlled study of the effect of forming pressure on distortion was conducted on type 162 glass plain weave fabrics. Panels (6 x 6 in) were produced via a resin infusion type setup, but with an EPON 815 epoxy resin. Pressures ranging from hand layup to 200 psi were used (vf: 34-54 percent). Photomicrographs indicated that at pressures up to 50 psi, large changes in thickness were due primarily to resin squeeze out. At higher pressures, when intimate contact was made between the layers, there was some tow flattening and in-plane shifting to optimize nesting. However, even at 200 psi the period and amplitude of the tow undulation remained constant, suggesting that for this relatively fine fabric, distortions from compaction were not a problem. Because of the interest in using larger tows (to reduce cost) and more complex structures, tests were also run on 2D triaxial glass braid (113 yd/lb at 0, 225 yd/lb at +/- 45). Forming pressures of 20, 50, 200, and 500 psi were used, and short block compression tests were run. The 500 psi specimen had a 10 percent decrease in modulus and an almost 50 percent decrease in strength (vs. 20 psi). Because the total fiber wgt/panel was kept constant, the thickness varied from 0.32 to 0.22 in (49-70 percent vf). Yet, the strength value is clearly below what would be expected, even with the decrease in thickness. Photomicrographs of these samples will be taken to determine if more fabric distortion exists in the 500 psi specimens. Finally, because the ultimate goal is to be able to predict and control distortion in a variety of textile structures, a model compaction test was developed to directly measure the deformation of the tows during compaction. Layers of dry glass fabric were placed in a mold with a clear plexiglass window. The yarn amplitude and period was then calculated using image analysis of the videotaped deformation. Preliminary tests demonstrated the feasibility of this technique for simple fabrics with large tows.

Chen, Julie↗

NASA NTRS1996

The Implications of ACTS Technology on the Requirements of Rain Attenuation Modeling for Communication System Specification and Analysis at 30/20 GHz and Beyond

The advent of the use of the Ka-Band for space communications, coupled with the introduction of digital modulation techniques as well as multiple-beam methodology for satellites, has deemed it necessary to reassess the plethora of rain attenuation prediction models in use. The Advanced Communication Technology Satellite (ACTS) Project, undertaken by the National Aeronautics and Space Administration in 1983, offered such challenges to rain attenuation prediction modeling. Up to 1983, no such single modeling formalism existed that could fill such requirements. Not even the work done by the NASA Propagation Experimenters (NAPEX) Group had envisioned such requirements, so no dynamic Ka-Band data existed from which one could draw conclusions. In this paper, the basic rudiments of what has become to be known as the 'ACTS Rain Attenuation Prediction Model' will be presented. The concept of rain fade mitigation control availability will be introduced. A new evaluation is then presented for the performance of satellite communication systems, in particular, those to be operating within the Ka-Band and above, that will necessarily employ some type of dynamic rain fade mitigation procedure.

Manning, Robert M.↗

NASA NTRS2005

Design and Testing of a Blended Wing Body With Boundary Layer Ingestion Nacelles at High Reynolds Numbers

A knowledge-based aerodynamic design method coupled with an unstructured grid Navier-Stokes flow solver was used to improve the propulsion/airframe integration for a Blended Wing Body with boundary-layer ingestion nacelles. A new zonal design capability was used that significantly reduced the time required to achieve a successful design for each nacelle and the elevon between them. A wind tunnel model was built with interchangeable parts reflecting the baseline and redesigned configurations and tested in the National Transonic Facility (NTF). Most of the testing was done at the cruise design conditions (Mach number = 0.85, Reynolds number = 75 million). In general, the predicted improvements in forces and moments as well as the changes in wing pressures between the baseline and redesign were confirmed by the wind tunnel results. The effectiveness of elevons between the nacelles was also predicted surprisingly well considering the crudeness in the modeling of the control surfaces in the flow code. A novel flow visualization technique involving pressure sensitive paint in the cryogenic nitrogen environment used in high-Reynolds number testing in the NTF was also investigated.

Campbell, Richard L.↗

NASA NTRS2006

Modeling and Classifying Six-Dimensional Trajectories for Teleoperation Under a Time Delay

Within the context of teleoperating the JSC Robonaut humanoid robot under 2-10 second time delays, this paper explores the technical problem of modeling and classifying human motions represented as six-dimensional (position and orientation) trajectories. A dual path research agenda is reviewed which explored both deterministic approaches and stochastic approaches using Hidden Markov Models. Finally, recent results are shown from a new model which represents the fusion of these two research paths. Questions are also raised about the possibility of automatically generating autonomous actions by reusing the same predictive models of human behavior to be the source of autonomous control. This approach changes the role of teleoperation from being a stand-in for autonomy into the first data collection step for developing generative models capable of autonomous control of the robot.

SunSpiral, Vytas↗

NASA NTRS1995

Neural node network and model, and method of teaching same

The present invention is a fully connected feed forward network that includes at least one hidden layer 16. The hidden layer 16 includes nodes 20 in which the output of the node is fed back to that node as an input with a unit delay produced by a delay device 24 occurring in the feedback path 22 (local feedback). Each node within each layer also receives a delayed output (crosstalk) produced by a delay unit 36 from all the other nodes within the same layer 16. The node performs a transfer function operation based on the inputs from the previous layer and the delayed outputs. The network can be implemented as analog or digital or within a general purpose processor. Two teaching methods can be used: (1) back propagation of weight calculation that includes the local feedback and the crosstalk or (2) more preferably a feed forward gradient decent which immediately follows the output computations and which also includes the local feedback and the crosstalk. Subsequent to the gradient propagation, the weights can be normalized, thereby preventing convergence to a local optimum. Education of the network can be incremental both on and off-line. An educated network is suitable for modeling and controlling dynamic nonlinear systems and time series systems and predicting the outputs as well as hidden states and parameters. The educated network can also be further educated during on-line processing.

Parlos, Alexander G.↗

NASA NTRS2006

Designing and Testing a Blended Wing Body with Boundary Layer Ingestion Nacelles

Carter, Melissa B.↗

NASA NTRS2015

Early Operations Flight Correlation of the Lunar Laser Communications Demonstration (LLCD) on the Lunar Atmosphere and Dust Environment Explorer (LADEE)

The Lunar Atmosphere and Dust Environment Explorer (LADEE) mission launched on September 7, 2013 with a one month cruise before lunar insertion. The LADEE spacecraft is a power limited, octagonal, composite bus structure with solar panels on all eight sides with four vertical segments per side and 2 panels dedicated to instruments. One of these panels has the Lunar Laser Communications Demonstration (LLCD), which represents a furthering of the laser communications technology demonstration proved out by the Lunar Reconnaissance Orbiter (LRO). LLCD increases the bandwidth of communication to and from the moon with less mass and power than LROs technology demonstrator. The LLCD Modem and Controller boxes are mounted to an internal cruciform composite panel and have no dedicated radiator. The thermal design relies on power cycling of the boxes and radiation of waste heat to the inside of the panels, which then reject the heat when facing cold space. The LADEE mission includes a slow roll and numerous attitudes to accommodate the challenging thermal requirements for all the instruments on board. During the cruise phase, the internal Modem and Controller avionics for LLCD were warmer than predicted by more than modeling uncertainty would suggest. This caused concern that if the boxes were considerably warmer than expected while off, they would also be warmer when operating and could limit the operational time when in lunar orbit. The thermal group at Goddard Space Flight Center evaluated the models and design for these critical avionics for LLCD. Upon receipt of the spacecraft models and audit was performed and data was collected from the flight telemetry to perform a sanity check of the models and to correlate to flight where possible. This paper describes the efforts to correlate the model to flight data and to predict the thermal performance when in lunar orbit and presents some lessons learned.

LADEE↗

DOE OSTI2020

Prediction for Pressure Differential Across HEPA Filter Media Based on Media Characteristics and Particle Size Distribution

A new method for predicting the pressure drop across High Efficiency Particulate Air (HEPA) filter media is proposed based upon mass deposited onto the filter and known physical characteristics of the filter media. Detailed are the methods used in conjunction with current filter loading models to predict the pressure drop, as well as tests conducted to validate the methods. The benefit of a prediction model for practical use lies in the manufacturing and service life of nuclear grade HEPA filters. HEPA filters for use in nuclear facilities have a prescribed expiration date and a maximum allowable operating pressure drop. Therefore, the ability to predict the pressure drop across a filter and relate it to an expected length of service time can enable a reduction in wasted filters. This will allow for more informed decisions to be made based upon the dictated life cycle of the filters. Also, understanding and predicting how the pressure drop of HEPA filter media behaves as a function of physical characteristics and loaded mass can assist in future design and manufacturing of filter media. Currently, most existing pressure drop models are either computationally based or analytical methods relying on data gathered during tests. Neither are practical for prediction; the computational methods are difficult to implement, and the current analytical methods are more useful as tools for analysis. The current analytical model developed by Bergman et al. is based upon the pressure drop from each media fiber and modeling the deposited particles as newly formed fibers. Using Bergman's model and the media properties, air properties, and known aerosol particle size distribution, a pressure drop curve as a function of loaded mass can be created. This curve implies initial loading in the depth of the filter media with a transition to pure surface loading on the filter face, and a sensitivity to an evolving particle size distribution as mass continues to load onto the filter. To implement the predictive model, knowledge of the mean filter fiber diameter and porosity of the filter media is required. Traditionally, the mean fiber diameter is calculated as an effective diameter from prior media testing, however, in this study a Scanning Electron Microscope (SEM) technique is used to acquire this variable. Validation of the predictive model is provided by flat sheet media tests under a controlled environment with a measured particle size distribution of the challenge aerosol and shows reasonable preliminary agreement.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

NASA NTRS1972

Thermal design verification testing for the ATS-F and -G spacecraft.

There is a wide fluctuation in the internal power dissipation from the components within the earth viewing module (EVM). The electronic component functional reliability required for a two-to-five year mission is the most significant factor for the thermal design criteria. A mathematical thermal model of the EVM and the orbital environment is used to predict the performance of the thermal control system. Comparisons of the results obtained in chamber thermal balance tests with the data computed on the basis of the theoretical model provide the means for validating the thermal design.

Coyle, M.↗

DOE OSTI2023

Domain-aware Control-oriented Neural Models for Autonomous Underwater Vehicles

Conventional physics-based modeling is a time-consuming bottleneck in control design for complex nonlinear systems like autonomous underwater vehicles (AUVs). In contrast, purely data-driven models, require a large number of observations and lack operational guarantees for safety-critical systems. Data-driven models leveraging available partially characterized dynamics have potential to provide reliable systems models in a typical data-limited scenario for high value complex systems, thereby avoiding months of expensive expert modeling time. In this work we explore this middle-ground between expert-modeled and pure data-driven modeling. We present control-oriented parametric models with varying levels of domain-awareness that exploit known system structure and prior physics knowledge to create constrained deep neural dynamical system models. We employ universal differential equations to construct data-driven blackbox and graybox representations of the AUV dynamics. In addition, we explore a hybrid formulation that explicitly models the residual error related to imperfect graybox models. We compare the prediction performance of the learned models for different distributions of initial conditions and control inputs to assess their suitability for control.

Shaw Cortez, Wenceslao E.↗

NASA NTRS1972

A wind-tunnel evaluation of analytical techniques for predicting static stability and control characteristics of flexible aircraft

An experimental evaluation of analytical techniques for predicting certain stability and control characteristics of a large flexible aircraft is presented. Analytical methods based on both the model approach and flexibility influence coefficients are developed to predict the aerodynamic characteristics of a flexible airplane. These methods are then applied to a flexibly scaled model of a supersonic transport configuration. Comparisons of wind-tunnel data, calculations based on the model approach, and flexibility influence coefficients are presented over the Mach number range from 0.6 to 2.7. An examination of the results obtained from this study indicates that both analytical techniques predict reasonably well the effect of flexibility on the basic longitudinal characteristics and that both techniques give generally comparable results.

Abel, I.↗

NASA NTRS1991

Knowledge-based Autonomous Test Engineer (KATE)

Mathematical models of system components have long been used to allow simulators to predict system behavior to various stimuli. Recent efforts to monitor, diagnose, and control real-time systems using component models have experienced similar success. NASA Kennedy is continuing the development of a tool for implementing real-time knowledge-based diagnostic and control systems called KATE (Knowledge based Autonomous Test Engineer). KATE is a model-based reasoning shell designed to provide autonomous control, monitoring, fault detection, and diagnostics for complex engineering systems by applying its reasoning techniques to an exchangeable quantitative model describing the structure and function of the various system components and their systemic behavior.

Parrish, Carrie L.↗

DOE OSTI2021

Progress on Optimizing Wind Farms and Rotor Designs Using Adjoints

Modern wind plants are increasingly tasked with multiple performance objectives. In addition to designing plants that maximize power output and minimize the levelized cost of energy (LCOE), the design and operation of wind plants is increasingly influenced by challenges regarding grid integration of variable generation renewables. This places a growing emphasis on making wind plants more controllable and predictable. WindSE is a Reynolds-averaged Navier-Stokes (RANS) model designed around analytical gradient and adjoint methods, with the ability to capture terrain-induced effects, as shown in Figure 1. The recent addition of an unsteady solver with an actuator line method (ALM) and ongoing work to enable massively parallel optimizations gives it a unique niche to explore coupled plant-level controls and design problems. This code is an open source python package built on the FEniCS framework that utilizes fast, parallel PETSc solvers to model fluid flow throughout wind-farm scale domains. Two recent studies performed using WindSE demonstrate the capability to optimize under a wide variety of flow conditions and objective functions. In the first, we present an optimization focused on modifying the layout of a wind farm with a fixed number of turbines for maximum total power output [1]. This study highlights the ability to quickly perform simulations using the steady Navier-Stokes solver combined with rotors represented as actuator disks while also stressing the importance of capturing terrain-induced effects. Gradient-based optimization using the RANS equations is viable due to the inclusion of efficiently computed adjoint derivatives. We interpret the physical results of the optimal layout and also discuss the computational cost of scaling to larger problems. In the second study, we present the capabilities of the unsteady Navier-Stokes solver, where rotor-blade profiles represented by actuator lines are optimized to enhance wake steering effects and overall power production [2]. We quantify the wind plant performance gains obtained from this type of simultaneous control co-design optimization as compared to optimizing the blade design and yaw independently. Figure 2 shows the differences between a baseline two-turbine system and an optimized system where we fine-tune the blade chord profile. Results and challenges from each study are quickly summarized and used to motivate the current development efforts within WindSE. Current and future work is focused on enabling higher-resolution studies with more degrees of freedom through parallelization of both the simulation and optimization algorithms. We present benchmarking results to show that WindSE performs well in both weak- and strong-scaling tests and further demonstrate that the optimizer obtains the same convergence rates in both shared- and distributed-memory environments. Using larger wind farms, we can study deep-array effects within an optimization context, allowing the use of objective functions that have been previously unstudied. As an example, we present ongoing work on a blockage metric which characterizes the loss of available kinetic energy due to wake effects from multiple upstream turbines.

adjoint optimization↗

DOE OSTI2020

Enhancement of Unsteady and 3D Aerodynamics Models using Machine Learning

Unsteady aerodynamics will be an important part of the floating wind turbines of the future operating under high shear across the rotor disk coupled with platform motion and atmospheric turbulence. We develop an unsteady aerodynamics and dynamic stall model using a long short-term memory variant of recurrent neural networks. The neural network model is trained using the oscillating airfoil data set from Ohio State University. The predictions from our machine learning (ML)-based model show good agreement with the experimental data and other state-of-the-art dynamic stall models for a wide range of airfoils, Reynolds numbers and reduced frequencies. In some cases the predictions are better than the Beddoes-Leishman model implementation in OpenFAST, when using the default coefficients. The ML-based model is also able to capture the key physics associated with dynamic stall, such as the precedence of moment stall before lift stall and cycle-to-cycle variations in the aerodynamic response. The new unsteady aerodynamics model is expected to improve prediction of fatigue loads for yaw-based wake-steering control scenarios in actuator-line and actuator-disc simulations of wind farms. Our methodology for training the ML-model provides a pathway for improving design level tools using high-fidelity computational fluid dynamics (CFD) simulations in the future.

17 WIND ENERGY↗

NASA NTRS2008

Optical Modeling Activities for NASA's James Webb Space Telescope (JWST): V. Operational Alignment Updates

This paper is part five of a series on the ongoing optical modeling activities for the James Webb Space Telescope (JWST). The first two papers discussed modeling JWST on-orbit performance using wavefront sensitivities to predict line of sight motion induced blur, and stability during thermal transients. The third paper investigates the aberrations resulting from alignment and figure compensation of the controllable degrees of freedom (primary and secondary mirrors), which may be encountered during ground alignment and on-orbit commissioning of the observatory, and the fourth introduced the software toolkits used to perform much of the optical analysis for JWST. The work here models observatory operations by simulating line-of-sight image motion and alignment drifts over a two-week period. Alignment updates are then simulated using wavefront sensing and control processes to calculate and perform the corrections. A single model environment in Matlab is used for evaluating the predicted performance of the observatory during these operations.

Howard, Joseph M.↗

DOE OSTI2025

Ecovoltaic solar energy development can promote grassland bird communities

Ecologically informed photovoltaic (PV) developments that co-prioritize PV electricity generation with ecosystem function (‘ecovoltaics’) have emerged as a promising land sharing strategy to minimize ecological conflicts associated with PV solar energy development. While habitat-focused ecovoltaic designs can conceptually benefit biodiversity by offsetting or enhancing impacts of PV development, foundational field research is needed to examine how wildlife respond to these novel ecosystems. We conducted passive acoustic monitoring (PAM) in 2023 and 2024 at 13 solar facilities and paired control sites to investigate avian community responses to ecovoltaic facilities in the Midwestern United States. Compared to control sites (row crop agricultural fields), we found that ecovoltaic sites supported more grassland bird species throughout a 17-week monitoring period between May and September. Grassland bird communities on ecovoltaic sites were also more stable than on agricultural controls, as measured by the Jaccard dissimilarity index. We also used PAM-based weekly species occurrences in an occupancy-modelling framework to investigate the influence of PV development and other landscape variables on grassland bird occupancy. 10 out of 13 modelled grassland bird species had greater predicted occupancy probabilities (ψ) on PV sites than control sites. Synthesis and applications. Our findings suggest that properly sited and developed ecovoltaic solar facilities in human altered landscapes can improve habitat for birds and other wildlife, but further research is needed to understand which species may benefit most from these novel ecosystems.

14 SOLAR ENERGY↗

NASA NTRS2001

Experimental Investigations of Generalized Predictive Control for Tiltrotor Stability Augmentation

A team of researchers from the Army Research Laboratory, NASA Langley Research Center (LaRC), and Bell Helicopter-Textron, Inc. have completed hover-cell and wind-tunnel testing of a 1/5-size aeroelastically-scaled tiltrotor model using a new active control system for stability augmentation. The active system is based on a generalized predictive control (GPC) algorithm originally developed at NASA LaRC in 1997 for un-known disturbance rejection. Results of these investigations show that GPC combined with an active swashplate can significantly augment the damping and stability of tiltrotors in both hover and high-speed flight.

Nixon, Mark W.↗

NASA NTRS2004

Comparison of Rolling Moment Characteristics During Roll Oscillations for a Low and a High Aspect Ratio Configuration

Improvements in testing and modeling of nonlinear and unsteady aerodynamic effects for flight dynamics predictions of vehicle performance is critical to enable the design and implementation of new, innovative vehicle concepts. Any configuration which exhibits significant flow separation, nonlinear aerodynamics, control interactions or attempts maneuvering through one or more conditions such as these is, at present, a challenge to test, model or predict flight dynamic responses prior to flight. Even in flight test experiments, adequate models are not available to study and characterize the complex nonlinear and time-dependent flow effects occurring during portions of the maneuvering envelope. Traditionally, airplane designs have been conducted to avoid these areas of the flight envelope. Better understanding and characterization of these flight regimes may not only reduce risk and cost of flight test development programs, but also may pave the way for exploitation of those characteristics that increase airplane capabilities. One of the hurdles is that the nonlinear/unsteady effects appear to be configuration dependent. This paper compares some of the dynamic aerodynamic stability characteristics of two very different configurations - representative of a fighter and a transport airplane - during dynamic body-axis roll wind tunnel tests. The fighter model shows significant effects of oscillation frequency which are not as apparent for the transport configuration.

Brandon, Jay M.↗