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At least 847 records · Page 47

Reconfigurable Control with Neural Network Augmentation for a Modified F-15 Aircraft

This paper describes the performance of a simplified dynamic inversion controller with neural network supplementation. This 6 DOF (Degree-of-Freedom) simulation study focuses on the results with and without adaptation of neural networks using a simulation of the NASA modified F-15 which has canards. One area of interest is the performance of a simulated surface failure while attempting to minimize the inertial cross coupling effect of a [B] matrix failure (a control derivative anomaly associated with a jammed or missing control surface). Another area of interest and presented is simulated aerodynamic failures ([A] matrix) such as a canard failure. The controller uses explicit models to produce desired angular rate commands. The dynamic inversion calculates the necessary surface commands to achieve the desired rates. The simplified dynamic inversion uses approximate short period and roll axis dynamics. Initial results indicated that the transient response for a [B] matrix failure using a Neural Network (NN) improved the control behavior when compared to not using a neural network for a given failure, However, further evaluation of the controller was comparable, with objections io the cross coupling effects (after changes were made to the controller). This paper describes the methods employed to reduce the cross coupling effect and maintain adequate tracking errors. The IA] matrix failure results show that control of the aircraft without adaptation is more difficult [leas damped) than with active neural networks, Simulation results show Neural Network augmentation of the controller improves performance in terms of backing error and cross coupling reduction and improved performance with aerodynamic-type failures.

Burken, John J.↗

Highly parallel sparse Cholesky factorization

Several fine grained parallel algorithms were developed and compared to compute the Cholesky factorization of a sparse matrix. The experimental implementations are on the Connection Machine, a distributed memory SIMD machine whose programming model conceptually supplies one processor per data element. In contrast to special purpose algorithms in which the matrix structure conforms to the connection structure of the machine, the focus is on matrices with arbitrary sparsity structure. The most promising algorithm is one whose inner loop performs several dense factorizations simultaneously on a 2-D grid of processors. Virtually any massively parallel dense factorization algorithm can be used as the key subroutine. The sparse code attains execution rates comparable to those of the dense subroutine. Although at present architectural limitations prevent the dense factorization from realizing its potential efficiency, it is concluded that a regular data parallel architecture can be used efficiently to solve arbitrarily structured sparse problems. A performance model is also presented and it is used to analyze the algorithms.

Gilbert, John R.↗

Applicability of Loads Estimation Techniques Using Sparse Acceleration Sensor Data to Spacecraft Structural Health Monitoring

The use of structural health monitoring systems on spacecraft structures can play a crucial role in ensuring the safety, reliability, and longevity of the structure by gathering and analyzing onboard sensor data. Of specific importance is monitoring for excessive loading at critical interfaces as any off-nominal structural excitations experienced by spacecraft structures can cause early unpredicted high structural life consumption or damage. The availability and cost of flight-certified sensors along with the size of spacecraft structures and allowable payload mass drives the need for a method to estimate loads using sparsely-located sensors. Numerous approaches such as physics-based, statistical learning, and physics-enhanced statistical learning algorithms have gained popularity among structural prognostics applications. However, developing noise-robust prediction models to assess loads and structural life predictions from a sparse multi-sensor data acquisition system can be a challenging task. This paper discusses the evaluation of physics-based versus machine-learning algorithms for predicting loads and structural life at mission critical locations on the spacecraft structure using a finite element loads analysis with the application of simulated noise and noise reduction techniques. To estimate the loads from accelerations, the physics-based algorithm leverages a loads transformation matrix from a Craig-Bampton reduced finite element model. A System Equivalent Reduction Expansion Process (SEREP) and a pseudo-inverse approach are considered to expand from the onboard sensor degrees of freedom to the Craig-Bampton model degrees of freedom. The machine learning algorithm provides a data driven solution/mapping of the sensor accelerations to the loads at the mission critical locations using a high dimensionality analysis. Although these strategies produce comparable loads prediction without noise, the limitations of these strategies with incorporating simulated noise and noise reduction techniques with low signal to noise ratio signals are evaluated. The study demonstrates the immense potential of statistical learning algorithms for sparse structural prognostic models and enhancing signal denoising techniques. These findings also highlight the need for noise-resilient prognostic models and low-noise data acquisition systems onboard spacecraft structures.

Spacecraft Structural Health Monitoring↗

Effect of model selection on combustor performance and stability predictions using ROCCID

The ROCket Combustor Interactive Design (ROCCID) methodology is an interactive computer program that combines previously developed combustion analysis models to calculate the combustion performance and stability of liquid rocket engines. Test data from 213 kN (48,000 lbf) Liquid Oxygen (LOX)/RP-1 combustor with an O-F-O (oxidizer-fuel-oxidizer) triplet injector were used to characterize the predictive capabilities of the ROCCID analysis models for this injector/propellant configuration. Thirteen combustion performance and stability models were incorporated into ROCCID, and ten of them, which have options for triplet injectors, were examined. Calculations using different combinations of analysis models, with little or no anchoring, were carried out on a test matrix of operating combinations matching those of the test program. Results of the computer analyses were compared to test data, and the ability of the model combinations to correctly predict combustion stability or instability was determined. For the best model combination(s), sensitivity of the calculations to fuel drop size and mixing efficiency was examined. Error in the stability calculations due to uncertainty in the pressure interaction index (N) was examined. The recommended model combinations for this O-F-O triplet LOX/RP-1 configuration are proposed.

Giuliani, James E.↗

Effect of model selection on combustor performance and stability using ROCCID

The ROCket Combustor Interactive Design (ROCCID) methodology is an interactive computer program that combines previously developed combustion analysis models to calculate the combustion performance and stability of liquid rocket engines. Test data from a 213 kN (48,000 lbf) Liquid Oxygen (LOX)/RP-1 combustor with a O-F-O (oxidizer-fuel-oxidizer) triplet injector were used to characterize the predictive capabilities of the ROCCID analysis models for this injector/propellant configuration. Thirteen combustion performance and stability models have been incorporated into ROCCID, and ten of them, which have options for triplet injectors, were examined in this study. Calculations using different combinations of analysis models, with little or no anchoring, were carried out on a test matrix of operating conditions matching those of the test program. Results of the computer analyses were compared to test data, and the ability of the model combinations to correctly predict combustion stability or instability was determined. For the best model combination(s), sensitivity of the calculations to fuel drop size and mixing efficiency was examined. Error in the stability calculations due to uncertainty in the pressure interaction index (N) was examined. The recommended model combinations for this O-F-O triplet LOX/RP-1 configuration are proposed.

Giuliani, James E.↗

Application of a Reduced Order Kalman Filter to Initialize a Coupled Atmosphere-Ocean Model: Impact on the Prediction of El Nino

A reduced order Kalman Filter, based on a simplification of the Singular Evolutive Extended Kalman (SEEK) filter equations, is used to assimilate observed fields of the surface wind stress, sea surface temperature and sea level into the nonlinear coupled ocean-atmosphere model of Zebiak and Cane. The SEEK filter projects the Kalman Filter equations onto a subspace defined by the eigenvalue decomposition of the error forecast matrix, allowing its application to high dimensional systems. The Zebiak and Cane model couples a linear reduced gravity ocean model with a single vertical mode atmospheric model of Zebiak. The compatibility between the simplified physics of the model and each observed variable is studied separately and together. The results show the ability of the model to represent the simultaneous value of the wind stress, SST and sea level, when the fields are limited to the latitude band 10 deg S - 10 deg N In this first application of the Kalman Filter to a coupled ocean-atmosphere prediction model, the sea level fields are assimilated in terms of the Kelvin and Rossby modes of the thermocline depth anomaly. An estimation of the error of these modes is derived from the projection of an estimation of the sea level error over such modes. This method gives a value of 12 for the error of the Kelvin amplitude, and 6 m of error for the Rossby component of the thermocline depth. The ability of the method to reconstruct the state of the equatorial Pacific and predict its time evolution is demonstrated. The method is shown to be quite robust for predictions up to six months, and able to predict the onset of the 1997 warm event fifteen months before its occurrence.

Ballabrera-Poy, J.↗

Microgravity Geyser and Flow Field Prediction

Modeling and prediction of flow fields and geyser formation in microgravity cryogenic propellant tanks was investigated. A computational simulation was used to reproduce the test matrix of experimental results performed by other investigators, as well as to model the flows in a larger tank. An underprediction of geyser height by the model led to a sensitivity study to determine if variations in surface tension coefficient, contact angle, or jet pipe turbulence significantly influence the simulations. It was determined that computational geyser height is not sensitive to slight variations in any of these items. An existing empirical correlation based on dimensionless parameters was re-examined in an effort to improve the accuracy of geyser prediction. This resulted in the proposal for a re-formulation of two dimensionless parameters used in the correlation; the non-dimensional geyser height and the Bond number. It was concluded that the new non-dimensional geyser height shows little promise. Although further data will be required to make a definite judgement, the reformulation of the Bond number provided correlations that are more accurate and appear to be more general than the previously established correlation.

Hochstein, J. I.↗

Improvement of structural models using covariance analysis and nonlinear generalized least squares

The next generation of large, flexible space structures will be too light to support their own weight, requiring a system of structural supports for ground testing. The authors have proposed multiple boundary-condition testing (MBCT), using more than one support condition to reduce uncertainties associated with the supports. MBCT would revise the mass and stiffness matrix, analytically qualifying the structure for operation in space. The same procedure is applicable to other common test conditions, such as empty/loaded tanks and subsystem/system level tests. This paper examines three techniques for constructing the covariance matrix required by nonlinear generalized least squares (NGLS) to update structural models based on modal test data. The methods range from a complicated approach used to generate the simulation data (i.e., the correct answer) to a diagonal matrix based on only two constants. The results show that NGLS is very insensitive to assumptions about the covariance matrix, suggesting that a workable NGLS procedure is possible. The examples also indicate that the multiple boundary condition procedure more accurately reduces errors than individual boundary condition tests alone.

Glaser, R. J.↗

Current Computational Challenges for CMC Processes, Properties, and Structures

In comparison to current state-of-the-art metallic alloys, ceramic matrix composites (CMC) offer a variety of performance advantages, such as higher temperature capability (greater than the approx.2100 F capability for best metallic alloys), lower density (approx.30-50% metal density), and lower thermal expansion. In comparison to other competing high-temperature materials, CMC are also capable of providing significantly better static and dynamic toughness than un-reinforced monolithic ceramics and significantly better environmental resistance than carbon-fiber reinforced composites. Because of these advantages, NASA, the Air Force, and other U.S. government agencies and industries are currently seeking to implement these advanced materials into hot-section components of gas turbine engines for both propulsion and power generation. For applications such as these, CMC are expected to result in many important performance benefits, such as reduced component cooling air requirements, simpler component design, reduced weight, improved fuel efficiency, reduced emissions, higher blade frequencies, reduced blade clearances, and higher thrust. Although much progress has been made recently in the development of CMC constituent materials and fabrication processes, major challenges still remain for implementation of these advanced composite materials into viable engine components. The objective of this presentation is to briefly review some of those challenges that are generally related to the need to develop physics-based computational approaches to allow CMC fabricators and designers to model (1) CMC processes for fiber architecture formation and matrix infiltration, (2) CMC properties of high technical interest such as multidirectional creep, thermal conductivity, matrix cracking stress, damage accumulation, and degradation effects in aggressive environments, and (3) CMC component life times when all of these effects are interacting in a complex stress and service environment. To put these computational issues in perspective, the various modeling needs within these three areas are briefly discussed in terms of their technical importance and their key controlling mechanistic factors as we know them today. Emphasis is placed primarily on the SiC/SiC ceramic composite system because of its higher temperature capability and enhanced development within the CMC industry. A brief summary is then presented concerning on-going property studies aimed at addressing these CMC modeling needs within NASA in terms of their computational approaches and recent important results. Finally an overview perspective is presented on those key areas where further CMC computational studies are needed today to enhance the viability of CMC structural components for high-temperature applications.

DiCarlo, James↗

An Empirical State Error Covariance Matrix Orbit Determination Example

State estimation techniques serve effectively to provide mean state estimates. However, the state error covariance matrices provided as part of these techniques suffer from some degree of lack of confidence in their ability to adequately describe the uncertainty in the estimated states. A specific problem with the traditional form of state error covariance matrices is that they represent only a mapping of the assumed observation error characteristics into the state space. Any errors that arise from other sources (environment modeling, precision, etc.) are not directly represented in a traditional, theoretical state error covariance matrix. First, consider that an actual observation contains only measurement error and that an estimated observation contains all other errors, known and unknown. Then it follows that a measurement residual (the difference between expected and observed measurements) contains all errors for that measurement. Therefore, a direct and appropriate inclusion of the actual measurement residuals in the state error covariance matrix of the estimate will result in an empirical state error covariance matrix. This empirical state error covariance matrix will fully include all of the errors in the state estimate. The empirical error covariance matrix is determined from a literal reinterpretation of the equations involved in the weighted least squares estimation algorithm. It is a formally correct, empirical state error covariance matrix obtained through use of the average form of the weighted measurement residual variance performance index rather than the usual total weighted residual form. Based on its formulation, this matrix will contain the total uncertainty in the state estimate, regardless as to the source of the uncertainty and whether the source is anticipated or not. It is expected that the empirical error covariance matrix will give a better, statistical representation of the state error in poorly modeled systems or when sensor performance is suspect. In its most straight forward form, the technique only requires supplemental calculations to be added to existing batch estimation algorithms. In the current problem being studied a truth model making use of gravity with spherical, J2 and J4 terms plus a standard exponential type atmosphere with simple diurnal and random walk components is used. The ability of the empirical state error covariance matrix to account for errors is investigated under four scenarios during orbit estimation. These scenarios are: exact modeling under known measurement errors, exact modeling under corrupted measurement errors, inexact modeling under known measurement errors, and inexact modeling under corrupted measurement errors. For this problem a simple analog of a distributed space surveillance network is used. The sensors in this network make only range measurements and with simple normally distributed measurement errors. The sensors are assumed to have full horizon to horizon viewing at any azimuth. For definiteness, an orbit at the approximate altitude and inclination of the International Space Station is used for the study. The comparison analyses of the data involve only total vectors. No investigation of specific orbital elements is undertaken. The total vector analyses will look at the chisquare values of the error in the difference between the estimated state and the true modeled state using both the empirical and theoretical error covariance matrices for each of scenario.

Frisbee, Joseph H., Jr.↗

Development of Matrix Microstructures in UHTC Composites

One of the major issues hindering the use of ultra high temperature ceramics for aerospace applications is low fracture toughness. There is considerable interest in developing fiber-reinforced composites to improve fracture toughness. Considerable knowledge has been gained in controlling and improving the microstructure of monolithic UHTCs, and this paper addresses the question of transferring that knowledge to composites. Some model composites have been made and the microstructures of the matrix developed has been explored and compared to the microstructure of monolithic materials in the hafnium diboride/silicon carbide family. Both 2D and 3D weaves have been impregnated and processed.

Johnson, Sylvia↗

Microstructural Influence on Deformation and Fatigue Life of Composites Using the Generalized Method of Cells

A fully coupled deformation and damage approach to modeling the response of composite materials and composite laminates is presented. It is based on the semi-­‐analytical generalized method of cells (GMC) micromechanics model as well as its higher fidelity counterpart, HFGMC, both of which provide closed-form constitutive equations for composite materials as well as the micro scale stress and strain fields in the composite phases. The provided constitutive equations allow GMC and HFGMC to function within a higher scale structural analysis (e.g., finite element analysis or lamination theory) to represent a composite material point, while the availability of the micro fields allow the incorporation of lower scale sub­‐models to represent local phenomena in the fiber and matrix. Further, GMC's formulation performs averaging when applying certain governing equations such that some degree of microscale field accuracy is surrendered in favor of extreme computational efficiency, rendering the method quite attractive as the centerpiece in a integrated computational material engineering (ICME) structural analysis; whereas HFGMC retains this microscale field accuracy, but at the price of significantly slower computational speed. Herein, the sensitivity of deformation and the fatigue life of graphite/epoxy PMC composites, with both ordered and disordered microstructures, has been investigated using this coupled deformation and damage micromechanics based approach. The local effects of fiber breakage and fatigue damage are included as sub‐models that operate on the microscale for the individual composite phases. For analysis of laminates, classical lamination theory is employed as the global or structural scale model, while GMC/HFGMC is embedded to operate on the microscale to simulate the behavior of the composite material within each laminate layer. A key outcome of this study is the statistical influence of microstructure and micromechanics idealization (GMC or HFGMC) on the overall accuracy of unidirectional and laminated composite deformation and fatigue response.

Microscale Models↗

A Spreadsheet Simulation Tool for Terrestrial and Planetary Balloon Design

During the early stages of new balloon design and development, it is necessary to conduct many trade studies. These trade studies are required to determine the design space, and aid significantly in determining overall feasibility. Numerous point designs then need to be generated as details of payloads, materials, mission, and manufacturing are determined. To accomplish these numerous designs, transient models are both unnecessary and time intensive. A steady state model that uses appropriate design inputs to generate system-level descriptive parameters can be very flexible and fast. Just such a steady state model has been developed and has been used during both the MABS 2001 Mars balloon study and the Ultra Long Duration Balloon Project. Using Microsoft Excel's built-in iteration routine, a model was built. Separate sheets were used for performance, structural design, materials, and thermal analysis as well as input and output sheets. As can be seen from figure 1, the model takes basic performance requirements, weight estimates, design parameters, and environmental conditions and generates a system level balloon design. Figure 2 shows a sample output of the model. By changing the inputs and a few of the equations in the model, balloons on earth or other planets can be modeled. There are currently several variations of the model for terrestrial and Mars balloons, as well there are versions of the model that perform crude material design based on strength and weight requirements. To perform trade studies, the Visual Basic language built into Excel was used to create an automated matrix of designs. This trade study module allows a three dimensional trade surface to be generated by using a series of values for any two design variables. Once the fixed and variable inputs are defined, the model automatically steps through the input matrix and fills a spreadsheet with the resulting point designs. The proposed paper will describe the model in detail, including current variations. The assumptions, governing equations, and capabilities will be addressed. Detailed examples of the model in practice will also be used.

Raquea, Steven M.↗

A math model for high velocity sensoring with a focal plane shuttered camera.

A new mathematical model is presented which describes the image produced by a focal plane shutter-equipped camera. The model is based upon the well-known collinearity condition equations and incorporates both the translational and rotational motion of the camera during the exposure interval. The first differentials of the model with respect to exposure interval, delta t, yield the general matrix expressions for image velocities which may be simplified to known cases. The exposure interval, delta t, may be replaced under certain circumstances with a function incorporating blind velocity and image position if desired. The model is tested using simulated Lunar Orbiter data and found to be computationally stable as well as providing excellent results, provided that some external information is available on the velocity parameters.

Morgan, P.↗

Effect of Cyclic Thermal Loads on Fatigue Reliability in Polymer Matrix Composites

Technological solutions that will ensure the economic viability and environmental compatibility of a future High Speed Civil Transport plane are currently being sought. Lighter structural materials for both airframe primary structures and engine structure components are being investigated. We believe that such objectives can be achieved through the use of high-temperature composites as well as other conventional, lighter weight alloys. One of the prime issues for these structural components is assured long-term behavior with a specified reliability. An investigation was conducted to describe a computational simulation methodology for predicting fatigue life, reliability, and probabilistic long-term behavior of polymer matrix composites. A unified time-, stress-, and load-dependent Multi- Factor Interaction Equation (MFIE) model developed at the NASA Lewis Research Center was used to simulate the long-term behavior of polymer matrix composites.

Chamis, Christos C.↗

Closed-Loop Evaluation of an Integrated Failure Identification and Fault Tolerant Control System for a Transport Aircraft

Formal robustness analysis of aircraft control upset prevention and recovery systems could play an important role in their validation and ultimate certification. Such systems developed for failure detection, identification, and reconfiguration, as well as upset recovery, need to be evaluated over broad regions of the flight envelope or under extreme flight conditions, and should include various sources of uncertainty. To apply formal robustness analysis, formulation of linear fractional transformation (LFT) models of complex parameter-dependent systems is required, which represent system uncertainty due to parameter uncertainty and actuator faults. This paper describes a detailed LFT model formulation procedure from the nonlinear model of a transport aircraft by using a preliminary LFT modeling software tool developed at the NASA Langley Research Center, which utilizes a matrix-based computational approach. The closed-loop system is evaluated over the entire flight envelope based on the generated LFT model which can cover nonlinear dynamics. The robustness analysis results of the closed-loop fault tolerant control system of a transport aircraft are presented. A reliable flight envelope (safe flight regime) is also calculated from the robust performance analysis results, over which the closed-loop system can achieve the desired performance of command tracking and failure detection.

Shin, Jong-Yeob↗

Investigation of Micro-Scale Architectural Effects on Damage of Composites

This paper presents a three-dimensional, energy based, anisotropic, stiffness reduction, progressive damage model for composite materials and composite material constituents. The model has been implemented as a user-defined constitutive model within the Abaqus finite element software package and applied to simulate the nonlinear behavior of a damaging epoxy matrix within a unidirectional composite material. Three different composite microstructures were considered as finite element repeating unit cells, with appropriate periodicity conditions applied at the boundaries. Results representing predicted transverse tensile, longitudinal shear, and transverse shear stress-strain curves are presented, along with plots of the local fields indicating the damage progression within the microstructure. It is demonstrated that the damage model functions appropriately at the matrix scale, enabling localization of the damage to simulate failure of the composite material. The influence of the repeating unit cell geometry and the effect of the directionality of the applied loading are investigated and discussed.

damage↗

Advanced Environmental Barrier Coating Development for SiC/SiC Ceramic Matrix Composites: NASA's Perspectives

This presentation reviews NASA environmental barrier coating (EBC) system development programs and the coating materials evolutions for protecting the SiC/SiC Ceramic Matrix Composites in order to meet the next generation engine performance requirements. The presentation focuses on several generations of NASA EBC systems, EBC-CMC component system technologies for SiC/SiC ceramic matrix composite combustors and turbine airfoils, highlighting the temperature capability and durability improvements in simulated engine high heat flux, high pressure, high velocity, and with mechanical creep and fatigue loading conditions. The current EBC development emphasis is placed on advanced NASA 2700F candidate environmental barrier coating systems for SiC/SiC CMCs, their performance benefits and design limitations in long-term operation and combustion environments. Major technical barriers in developing environmental barrier coating systems, the coating integrations with next generation CMCs having the improved environmental stability, erosion-impact resistance, and long-term fatigue-environment system durability performance are described. The research and development opportunities for advanced turbine airfoil environmental barrier coating systems by utilizing improved compositions, state-of-the-art processing methods, and simulated environment testing and durability modeling are discussed.

Ceramic Matrix Composites↗