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Viewgraphs on a neurocomputing approach to model determination of large space structures are presented. Topics covered include: background on neural networks; math modeling with neural networks; computer architectures for real-time modeling; and hardware and software implementation considerations, OPTIMA/1 data acquisition, modeling, and control workstation.
Similitude requirements in scale model determination of shell buckling under impulsive pressures
The Application of Machine-learning Algorithms for On-board Asteroid Shape Model Determination project will develop an innovative system for spacecraft navigation to expand the capability of small spacecraft to meet the critical challenges associated with small-body exploration. Such challenges include accurate navigation in a microgravity environment and precision targeting of particular locations on an asteroid surface for sample collection. This on-board system will cut the computational "umbilical" back to Earth-currently necessary for the generation of a global shape model that requires thousands of images with sufficient resolution and adequate variation of incidence and emission angles, processed manually by a team of experts on Earth for several months. Small satellites have limited bandwidth and are unable to downlink the data volume required for this processing, restricting their ability to perform deep-space asteroid exploration.
The fundamental challenge in identification of nonlinear dynamic systems is determining the appropriate form of the model. A robust technique is presented which essentially eliminates this problem for many applications. The technique is based on the Minimum Model Error (MME) optimal estimation approach. A detailed literature review is included in which fundamental differences between the current approach and previous work is described. The most significant feature is the ability to identify nonlinear dynamic systems without prior assumption regarding the form of the nonlinearities, in contrast to existing nonlinear identification approaches which usually require detailed assumptions of the nonlinearities. Model form is determined via statistical correlation of the MME optimal state estimates with the MME optimal model error estimates. The example illustrations indicate that the method is robust with respect to prior ignorance of the model, and with respect to measurement noise, measurement frequency, and measurement record length.
Aircraft engine components invariably are subjected to mean stresses over and above the cyclic loads. In monolithic materials, it has been observed that tensile mean stresses are detrimental and compressive mean stresses are beneficial to fatigue life in comparison to a base of zero mean stress. Several mean stress models exist for monolithic metals, but each differ quantitatively in the extent to which detrimental or beneficial effects are ascribed. There have been limited attempts to apply these models to metal matrix composites. At the NASA Lewis Research Center, several mean stress models--the Smith-Watson- Topper, Walker, Normalized Goodman, and Soderberg models--were examined for applicability to this class of composite materials. The Soderberg approach, which normalizes the mean stress to a 0.02-percent yield strength, was shown to best represent the effect of mean stresses over the range covered. The other models varied significantly in their predictability and often failed to predict the composite behavior at very high tensile mean stresses. This work is the first to systematically demonstrate the influence of mean stresses on metal matrix composites and model their effects. Attention also was given to fatigue-cracking mechanisms in the Ti-15-3 matrix and to micromechanics analyses of mean stress effects.
Large uncertainties in North American terrestrial carbon fluxes hinder regional climate projections. Terrestrial biosphere models (TBMs), the essential tools for understanding continental-scale carbon cycle, diverge on whether temperate forests or croplands dominate carbon uptake in North America. Evidence from novel photosynthetic proxies, such as those based on chlorophyll fluorescence, has cast doubt on the “weak cropland, strong forest” carbon uptake patterns simulated by most TBMs. However, no systematic evaluation of TBMs has yet been attempted to pin down space-time patterns that are most consistent with regional CO 2 observational constraints. Here, we leverage atmospheric CO 2 observations and satellite-observed photosynthetic proxies to understand emergent space-time patterns in North American carbon fluxes from a large suite of TBMs and data-driven models. To do so, we evaluate how well the atmospheric signals resulting from carbon flux estimates reproduce the space-time variability in atmospheric CO 2 , as is observed by a network of continuous-monitoring towers over North America. Models with gross or net carbon fluxes that are consistent with the observed CO 2 variability share a salient feature of growing-season carbon uptake in Midwest US croplands. Conversely, the remaining models place most growing-season uptake in boreal or temperate forests. Differences in model explanatory power depend mainly on the simulated annual cycles of cropland uptake—especially, the timing of peak uptake—rather than the distribution of annual mean fluxes across biomes. Our results suggest that improved model representation of cropland phenology is crucial to robust, policy-relevant estimation of North American carbon exchange.
Total aerodynamic forces and moments of free flying body in wind tunnel determined from accelerations measured and telemetered by onboard instruments
CISLUNAR is a stand-alone computer program designed to generate the trajectory of a low-thrust spacecraft travelling in Earth-Moon space. The program allows the creation of functional trajectories dependent on the supplied spacecraft characteristics. The trajectory generation is a user interactive process. The original intent was for the program user to modify the necessary control values until a staisfactory trajectory has been created.
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The possibility of determining O(5+) outflow velocities by using a Doppler dimming analysis of the resonantly scattered intensities of O VI lambda 1031.9 and lambda 1037.6 is addressed. The technique is sensitive to outflow velocities, W, in the range W greater than 30 and less than 250 km/s and can be used for probing regions of the inner solar corona, where significant coronal heating and solar wind acceleration may be occurring. These velocity measurements, when combined with measurements of other plasma parameters (temperatures and densities of ions and electrons) can be used to estimate the energy and mass flux of O(5+). In particular, it may be possible to locate where the flow changes from subsonic to supersonic and to identify source regions for the high and low speed solar wind. The velocity diagnostic technique is discussed with emphasis placed on the requirements needed for accurate outflow velocity determinations. Model determinations of outflow velocities based on simulated Doppler observations are presented.
A procedure for airplane model structure determination from flight data based on modified stepwise regression (MSR), several decision criteria and postulated aerodynamic model equations is presented. The MSR is constructed to force a linear model for the aerodynamic coefficient first, then select significant nonlinear terms and reject nonsignificant terms from the model. In addition to the statistical criteria in the stepwise regression, the prediction sum of squares (PRESS) criterion and analysis of residuals are examined for the selection of an adequate model. The procedure is used in examples with simulated and real flight data. It is shown that the MSR performs better than the ordinary stepwise regression and that the technique can be also applied to the large amplitude maneuvers.
Models of the TOPEX/Poseidon spacecraft are developed by means of finite-element analyses for use in generating acceleration histories for various orbit orientations which account for nonconservative radiation forces. The acceleration profiles are developed with an analysis based on the use of the 'box-wing' model in which the satellite is modeled as a combination of flat plates. The models account for the effects of solar, earth-albedo, earth-IR, and spacecraft-thermal radiation. The finite-element analysis gives the total force and induced accelerations acting on the satellite. The plate types used in the analysis have parameters that can be adjusted to optimize model performance according to the micromodel analysis and tracking observations. Acceleration related to solar radiation pressure is modeled effectively, and the techniques are shown to be useful for the precise orbit determinations required for spacecraft such as the TOPEX/Poseidon.
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Determining the range of validity of Migdal’s approximation for electron-phonon (e-ph) coupled systems is a long-standing problem. Many attempts to answer this question employ the Holstein Hamiltonian, where the electron density couples linearly to local lattice displacements. When these displacements are large, however, nonlinear corrections to the interaction must also be included, which can significantly alter the physical picture obtained from this model. Using determinant quantum Monte Carlo and the self-consistent Migdal approximation, we compared superconducting and charge-density-wave correlations in the Holstein model with and without second-order nonlinear interactions. We find a disagreement between the two cases, even for relatively small values of the e-ph coupling strength, and, importantly, that this can occur in the same parameter regions where Migdal’s approximation holds. Our results demonstrate that questions regarding the validity of Migdal’s approximation go hand in hand with questions of the validity of a linear e-ph interaction.
The successful parametric modeling of the aerodynamics for an airplane operating at high angles of attack or sideslip is performed in two phases. First the aerodynamic model structure must be determined and second the associated aerodynamic parameters (stability and control derivatives) must be estimated for that model. The purpose of this paper is to document two versions of a stepwise regression computer program which were developed for the determination of airplane aerodynamic model structure and to provide two examples of their use on computer generated data. References are provided for the application of the programs to real flight data. The two computer programs that are the subject of this report, STEP and STEPSPL, are written in FORTRAN IV (ANSI l966) compatible with a CDC FTN4 compiler. Both programs are adaptations of a standard forward stepwise regression algorithm. The purpose of the adaptation is to facilitate the selection of a adequate mathematical model of the aerodynamic force and moment coefficients of an airplane from flight test data. The major difference between STEP and STEPSPL is in the basis for the model. The basis for the model in STEP is the standard polynomial Taylor's series expansion of the aerodynamic function about some steady-state trim condition. Program STEPSPL utilizes a set of spline basis functions.
Analytical model of turbine-type flowmeter guides in the selection of valid extrapolation of available calibration data. An expression for flowmeter performance is developed to include the effects of fluid friction, bearing drag, and magnetic drag upon helical rotor design.