Branched trajectory optimization by the projected gradient technique
Branched trajectory optimization for split rocket vehicles using projected gradient or steepest descent method
Gera, J.↗
SEARCH · Engineering Papers
Results for “gradient methods”
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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Optimization of RAE satellite boom deployment timing
Radio Astronomy Explorer satellite boom deployment method resulting in gravity gradient capture, emphasizing role of predeployment attitude and antenna Vee angle
Bowers, E. J., Jr.↗
Computer program calculates transonic velocities in turbomachines
Computer program, TSONIC, combines velocity gradient and finite difference methods to obtain numerical solution for ideal, transonic, compressible flow for axial, radial, or mixed flow cascade of turbomachinery blades.
Katsanis, T.↗
Recent developments in a wind tunnel magnetic balance.
A functional description of a prototype six component magnetic balance system for wind tunnel application is presented. The relationship of forces and moments on a ferromagnetic body to applied magnetic fields and gradients is shown. The method of producing the required fields in the prototype balance, its magnet arrangement and its performance are discussed. Aerodynamic data obtained with this balance on several model geometries are presented and compared with wind tunnel and ballistic range results.
Stephens, T.↗
Evaluation of analytical procedures for prediction of turbulent boundary layers on a porous wall
An analytical study has been made to determine how well current boundary layer prediction techniques work when there is mass transfer normal to the wall. The data that were considered in this investigation were for two-dimensional, incompressible, turbulent boundary layers with suction and blowing. Some of the bleed data were taken in an adverse pressure gradient. An integral prediction method was used three different porous wall skin friction relations, in addition to a solid-surface relation for the suction cases. A numerical prediction method was also used. Comparisons were made between theoretical and experimental skin friction coefficients, displacement and momentum thicknesses, and velocity profiles. The integral method with one of the porous wall skin friction laws gave very good agreement with data for most of the cases considered. The use of the solid-surface skin friction law caused the integral to overpredict the effectiveness of the bleed. The numerical techniques also worked well for most of the cases.
Towne, C. E.↗
Techniques for the processing of remotely sensed imagery
The following techniques are considered for classifying low resolution satellite imagery: (1) Gradient operations; (2) histogram methods; (3) gray level detection; (4) frequency domain operations; (5) Hadamard transform in digital image matching; and (6) edge and line detection schemes.
Deutsch, E. S.↗
Computational aspects of maximum likelihood estimation and reduction in sensitivity function calculations
This paper discusses numerical aspects of computing maximum likelihood estimates for linear dynamical systems in state-vector form. Different gradient-based nonlinear programming methods are discussed in a unified framework and their applicability to maximum likelihood estimation is examined. The problems due to singular Hessian or singular information matrix that are common in practice are discussed in detail and methods for their solution are proposed. New results on the calculation of state sensitivity functions via reduced order models are given. Several methods for speeding convergence and reducing computation time are also discussed.
Gupta, N. K.↗
Skylab investigation of the upwelling off the Northwest coast of Africa
The upwelling off the NW coast of Africa in the vicinity of Cape Blanc was studied in February - March 1974 from aircraft and in September 1973 from Skylab. The aircraft study was designed to determine the effectiveness of a differential radiometer in quantifying surface chlorophyll concentrations. Photographic images of the S190A Multispectral Camera and the S190B Earth Terrain Camera from Skylab were used to study distributional patterns of suspended material and to locate ocean color boundaries. The thermal channel of the S192 Multispectral Scanner was used to map sea-surface temperature distributions offshore of Cape Blanc. Correlating ocean color changes with temperature gradients is an effective method of qualitatively estimating biological productivity in the upwelling region off Africa.
Szekielda, K. H.↗
Basic principles of coaxial launch technology
Already in the 1930s, a discrete-coil mechanically synchronized launcher was built. At the present time, research is almost entirely directed towards railguns. However, although coaxial accelerators are more complex than railguns, they have certain unique advantages. Some of these advantages are related to the absence of physical contact requirements with the projectile, the possibility of a scale-up to very large projectile size, and the availability of up to 100 times more thrust for a given current. The price of the advantages is the need for a drive current in the form of pulses synchronized precisely with transit of each projectile coil through each drive coil. At high velocities, high voltages are required, and high voltage switching represents the technology limit on launch velocity. Attention is given to inductance gradients, the double hump, methods of excitation, methods of synchronization, projectile configuration, energy supply, fundamental limits, trends, and research needs.
Kolm, H.↗
Estimation of surface moisture availability from remote temperature measurements
Analysis of moisture availability, determined from GOES IR surface temperature measurements and a boundary layer model, and antecedent precipitation are presented for data taken over Texas and Argentina. Correlations between antecedent precipitation and moisture availability are high where the spatial variation in moisture availability is much larger than an inherent uncertainty in the method, which is judged to be about + or - 0.2 for the moisture availability parameter. In regions where there are large gradients of precipitation, the IR method can provide useful information on variations in soil moisture availability and, by implication, in precipitation.
Flores, Alberto L.↗
Thermomechanical deformation testing and modeling in the presence of metallurgical instabilities
A number of viscoplastic constitutive models were developed to describe deformation behavior under complex combinations of thermal and mechanical loading. Questions remain, however, regarding the validity of procedures used to characterize these models for specific structural alloys. One area of concern is that the majority of experimental data available for this purpose are determined under isothermal conditions. This experimental study is aimed at determining whether viscoplastic constitutive theories characterized using an isothermal data base can adequately model material response under the complex thermomechanical loading conditions typical of power generation service. The approach adopted was to conduct a series of carefully controlled thermomechanical experiments on a nickel-based superalloy, Hastelloy Alloy X. Previous investigations had shown that this material experiences metallurgical instabilities leading to complex hardening behavior, termed dynamic strain aging. Investigating this phenomenon under full thermomechanical conditions leads to a number of challenging experimental difficulties which up to the present work were unresolved. To correct this situation, a number of advances were made in thermomechanical testing techniques. Advanced methods for dynamic temperature gradient control, phasing control and thermal strain compensation were developed and incorporated into real time test control software. These advances allowed the thermomechanical data to be analyzed with minimal experimental uncertainty. The thermomechanical results were evaluated on both a phenomenological and microstructural basis. Phenomenological results revealed that the thermomechanical hardening trends were not bounded by those displayed under isothermal conditions. For the case of Hastelloy Alloy X (and similar dynamic strain aging materials), this strongly suggests that some form of thermomechanical testing is necessary when characterizing a thermoviscoplastic deformation model. Transmission electron microscopy was used to study the microstructural physics, and analyze the unique phenomenological behavior.
Castelli, Michael G.↗
Instabilities of two-dimensional inviscid compressible vortices
An investigation of the linear stability and subsequent nonlinear evolution and acoustic radiation of a planar inviscid compressible vortex is presented. The effects of the entropy gradient are investigated, and for the particular entropy profile chosen, the positive average entropy in the vortex core is destabilizing, while the opposite is true for the negative average entropy gradient. Finite-difference methods are used to study the linear initial value problem. These methods are found to be capable of accurately computing the frequencies and weak growth rates of the normal modes. When the initial condition consists of random perturbations, the long-time behavior is found to correspond to the most unstable normal mode in all cases. The numerical solution of the Euler equations is used to study the nonlinear development of an elliptic-mode perturbation.
Chan, W. M.↗
Expanded Equations for Torque and Force on a Cylindrical Permanent Magnet Core in a Large-Gap Magnetic Suspension System
The expanded equations for torque and force on a cylindrical permanent magnet core in a large-gap magnetic suspension system are presented. The core is assumed to be uniformly magnetized, and equations are developed for two orientations of the magnetization vector. One orientation is parallel to the axis of symmetry, and the other is perpendicular to this axis. Fields and gradients produced by suspension system electromagnets are assumed to be calculated at a point in inertial space which coincides with the origin of the core axis system in its initial alignment. Fields at a given point in the core are defined by expanding the fields produced at the origin as a Taylor series. The assumption is made that the fields can be adequately defined by expansion up to second-order terms. Examination of the expanded equations for the case where the magnetization vector is perpendicular to the axis of symmetry reveals that some of the second-order gradient terms provide a method of generating torque about the axis of magnetization and therefore provide the ability to produce six-degree-of-freedom control.
Groom, Nelson J.↗
The Effect of Strain Rate on the Evolution of Plane Wakes Subjected to Irrotational Strains
Direct numerical simulations of time-evolving turbulent plane wakes developing in the presence of irrotational plane strain applied at three different strain rates have been generated. The strain geometry is such that the flow is compressed in the streamwise direction and expanded in the cross-stream direction with the spanwise direction being unstrained. This geometry is the temporally evolving analogue of a spatially evolving wake in an adverse pressure gradient. A pseudospectral numerical method with up to 16 million modes is used to solve the equations in a reference frame moving with the irrotational strain. The initial condition for each simulation is taken from a previous turbulent self-similar plane wake direct numerical simulation at a velocity deficit Reynolds number, Re, of about 2,000. Although the evolutions of many statistics are nearly collapsed when plotted against total strain, there are some differences owing to the different strain rate histories. The impact of strain-rate on the wake spreading rate, the peak velocity deficit, the Reynolds stress profiles, and the flow structure is examined.
Rogers, Michael M.↗
Biodiversity within hot spring microbial mat communities: molecular monitoring of enrichment cultures
We have begun to examine the basis for incongruence between hot spring microbial mat populations detected by cultivation or by 16S rRNA methods. We used denaturing gradient gel electrophoresis (DGGE) to monitor enrichments and isolates plated therefrom. At near extincting inoculum dilutions we observed Chloroflexus-like and cyanobacterial populations whose 16S rRNA sequences have been detected in the 'New Pit' Spring Chloroflexus mat and the Octopus Spring cyanobacterial mat. Cyanobacterial populations enriched from 44 to 54 degrees C and 56 to 63 degrees C samples at near habitat temperatures were similar to those previously detected in mat samples of comparable temperatures. However, a lower temperature enrichment from the higher temperature sample selected for the populations found in the lower temperature sample. Three Thermus populations detected by both DGGE and isolation exemplify even more how enrichment may bias our view of community structure. The most abundant population was adapted to the habitat temperature (50 degrees C), while populations adapted to 65 degrees C and 70 degrees C were 10(2)- and 10(4)-fold less abundant, respectively. However, enrichment at 70 degrees C favored the least abundant strain. Inoculum dilution and incubation at the habitat temperature favored the more numerically relevant populations. We enriched many other aerobic chemoorganotrophic populations at various inoculum dilutions and substrate concentrations, most of whose 16S rRNA sequences have not been detected in mats. A common feature of numerically relevant cyanobacterial, Chloroflexus-like and aerobic chemorganotrophic populations, is that they grow poorly and resist cultivation on solidified medium, suggesting plating bias, and that the medium composition and incubation conditions may not reflect the natural microenvironments these populations inhabit.
Non-NASA Center↗
A Novel Machine Learning Method for Surface PM2.5 Estimations from Geostationary Satellites
Particulate matter (PM) with a diameter of less or equal to 2.5 μm, known as PM , affects human health as it penetrates the respiratory system. The Environmental Protection Agency (EPA) measures the atmospheric concentration of PM using air quality monitors stationed throughout the Continental United States (CONUS). Such measurements are points on a spatial domain and therefore, might not be representative of the air quality at nearby areas considering that the composition of the atmosphere is highly variable from place to place. Satellite based AOD permits a spatially uniform means of estimating PM and new geostationary satellites provide high temporal and spatial resolution estimation of AOD. However, the concentration of PM is non-linearly dependent on other atmospheric parameters that include relative humidity, temperature, and height of the planetary boundary layer. This information may be estimated at similar spatial and temporal resolutions as AOD from numerical modeling such as from the National Oceanic and Atmospheric Administration’s (NOAA) High Resolution Rapid Refresh (HRRR) model which resolves near real-time atmospheric conditions over the CONUS. The estimation of PM concentration is a multi-parametric problem that considers the effect of temporal dependencies among the different parameters. Deep learning approaches are appropriate for such complex estimation problems as they intrinsically capture relations among multiple non-linear parameters. This study compares deep-learning methods to traditional regression analysis to demonstrate the capabilities of these methods in predicting PM2.5 concentrations. Additionally, a novel ensemble learning approach is employed to identify scientific processes that could further improve the estimation of PM concentration. Utilizing Long Short-Term Memory (LSTM) neural networks, which are suitable for multivariate time series estimation problems as they are capable of learning long-term dependencies, individual models are created for each EPA station and trained on the aforementioned dataset collocated over each station. Individual station models are merged if the model's performance is improved by reducing the root mean squared error (RMSE) metric. This ensemble training method ultimately reduces the RMSE value. Evaluation of these results provide insights into physical processes and related observable parameters that may contribute to PM concentrations. Identified parameters evaluated to be statistically different between the merged and unmerged models are expected to improve overall performance. These new parameters are then utilized for reevaluation of the deep learning methods with an extreme gradient boosting model with an RMSE of 5.5 providing the best results.
George Priftis↗
Structural Model Tuning Tool: User's Reference Manual
This report presents an efficient approach for tuning finite element models to match the measured ground vibration test and static test data. Frequencies, mode shapes, total weight, location of the center of gravity, and static deformation computed from the finite element model are matched to the measured data. The model tuning procedure used in this work is based on solving an optimization problem in which the errors for the considered metrics, between the finite element prediction and the measured data, are minimized. Analytical sensitivity values of performance indices are computed using the NASTRAN-generated sensitivity values together with the in-house computer codes, which allow for faster computational time and the use of gradient-based optimizers. The method is applied to the Aerostructures Test Wing IV model. The study shows that the military standard and the National Aeronautics and Space Administration standard for comparing analytical and experimental modal data are all satisfied. The final finite element model correlates well with the test data. The flutter speed decreases by 8.91 percent after model tuning compared with the original Aerostructures Test Wing IV design.
Chan-gi Pak↗
A Bayesian Learning Approach to Wireless Outdoor Heatmap Construction using Deep Gaussian Process
We present a novel Bayesian learning approach to outdoor radio heatmap construction utilizing deep Gaussian process (GP). The proposed approach employs a two-layer hierarchy which consists of two cascaded Gaussian processes that are capable of modeling more complex input-output relations than standard single-layer Gaussian processes. Since deriving the exact model likelihood is challenging, a lower bound is optimized instead so that gradient descent-based methods can be performed to find out the optimal model parameters. Typically, inducing points are used in GPs to facilitate low-rank approximation of covariance (kernel) matrices for computation speedup. However, the inaccuracy induced by inducing points can accumulate when stacking multiple layers of GP which may hinder the performance of deep GP. Moreover, since inducing points need to be learned, having them at all layers of deep GP also incurs computational burden. To overcome the above challenges, in contrast to the canonical deep GP model, we use a modified architecture where a full standard GP resides in the first layer and inducing points are only introduced for the second layer. This modified architecture strikes a balance between model accuracy and training complexity. In the proposed model, the noise parameter of the first GP layer is also eliminated to improve the training efficiency as the noise parameter at the output of the second layer suffices to model the uncertainty in the output. The proposed approach is evaluated on real-world datasets, in the form of location-Received Signal Strength (RSS) pairs, collected from the Platform for Open Wireless Data-driven Experimental Research (POWDER) located at the campus of the University of Utah. Experiment results show that the proposed approach can achieve smaller prediction errors on various training and testing data configurations than DNN-based and GP-based methods.
46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗