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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 451 records · Page 25
All sourcesNASA NTRSDOE OSTI
NASA NTRS1993

Optimization of the Processing Parameters of High Temperature Superconducting Glass-Ceramics: Center Director's Discretionary Fund Final Report

A number of promising glass forming compositions of high Tc superconducting Ba-Sr-Ca-Cu-O (BSCCO) materials were evaluated for their glass-ceramic crystallization ability. The BSCCO ceramics belonging to the class of superconductors in the Ba-Sr-Ca-Cu-O system were the focus of this study. By first forming the superconducting material as a glass, subsequent devitrification into the crystalline (glass-ceramic) superconductor can be performed by thermal processing of the glass preform body. Glass formability and phase formation were determined by a variety of methods in another related study. This study focused on the nucleation and crystallization of the materials. Thermal analysis during rapid cooling aids in the evaluation of nucleation and crystallization behavior. Melt viscosity is used to predict glass formation ability.

Ethridge, E. C.↗
NASA NTRS2006

Heat Transfer of Thermocapillary Convection in a Two-Layered Fluid System Under the Influence of Magnetic Field

Heat transfer of a two-layer fluid system has been of great importance in a variety of industrial applications. For example, the phenomena of immiscible fluids can be found in materials processing and heat exchangers. Typically in solidification from a melt, the convective motion is the dominant factor that affects the uniformity of material properties. In the layered flow, thermocapillary forces can come into an important play, which was first emphasized by a previous investigator in 1958. Under extraterrestrial environments without gravity, thermocapillary effects can be a more dominant factor, which alters material properties in processing. Control and optimization of heat transfer in an immiscible fluid system need complete understanding of the flow phenomena that can be induced by surface tension at a fluid interface. The present work is focused on understanding of the magnetic field effects on thermocapillary convection, in order to optimize material processing. That is, it involves the study of the complicated phenomena to alter the flow motion in crystal growth. In this effort, the Marangoni convection in a cavity with differentially heated sidewalls is investigated with and without the influence of a magnetic field. As a first step, numerical analyses are performed, by thoroughly investigating influences of all pertinent physical parameters. Experiments are then conducted, with preliminary results, for comparison with the numerical analyses.

Ramachandran, N.↗
NASA NTRSDate not supplied

Copernicus-LinCov (COPCOV) Software Integration in Support of Robust Trajectory Optimization

Robust trajectory optimization is the process of optimizing a trajectory while accounting for system uncertainty due to a variety of potential error sources. This work highlights the development and features of a novel tool known as CopCov to support robust trajectory optimization efforts. CopCov acts as an interface between Copernicus, a generalized trajectory design and optimization tool, and LinCov, a linear covariance analysis tool. By having a direct interface between these two software packages, Copernicus can receive covariance information from LinCov through a direct feedback loop, thus enabling optimization of a trajectory that is robust to trajectory dispersions and navigation errors. This paper details the architecture of CopCov and its flexibility to operate under varying configurations, including with both tools running locally or alternatively with the tools communicating via a remote connection. Additionally, the CopCov tool is demonstrated on a simple Hohmann transfer reference trajectory with varying numbers of Trajectory Correction Maneuvers (TCMs) and varying problem formulations. This example scenario is used to highlight how the inclusion of the CopCov interface affects burn placement of both major burns and minor burns (i.e., TCMs) in the optimized solution. Results are compared against analytical solutions and against a Genetic Algorithm (GA) optimizer for independent verification and validation.

Copernicus↗
NASA NTRS1987

Efficient optimization of integrated aerodynamic-structural design

The introduction of composite materials is having a profound effect on the design process. Because these materials permit the designer to tailor material properties to improve structural, aerodynamic and acoustic performance, they require a more integrated multidisciplinary design process. Because of the complexity of the design process numerical optimization methods are required. The present paper is focused on a major difficulty associated with the multidisciplinary design optimization process - its enormous computational cost. We consider two approaches for reducing this computational burden: (1) development of efficient methods for cross-sensitivity calculation using perturbation methods; and (2) the use of approximate numerical optimization procedures. Our efforts are concentrated upon combined aerodynamic-structural optimization. Results are presented for the integrated design of a sailplane wing. The impact of our computational procedures on the computational costs of integrated costs of integrated designs are discussed.

Haftka, R. T.↗
NASA NTRS1998

Two-Dimensional High-Lift Aerodynamic Optimization Using Neural Networks

The high-lift performance of a multi-element airfoil was optimized by using neural-net predictions that were trained using a computational data set. The numerical data was generated using a two-dimensional, incompressible, Navier-Stokes algorithm with the Spalart-Allmaras turbulence model. Because it is difficult to predict maximum lift for high-lift systems, an empirically-based maximum lift criteria was used in this study to determine both the maximum lift and the angle at which it occurs. The 'pressure difference rule,' which states that the maximum lift condition corresponds to a certain pressure difference between the peak suction pressure and the pressure at the trailing edge of the element, was applied and verified with experimental observations for this configuration. Multiple input, single output networks were trained using the NASA Ames variation of the Levenberg-Marquardt algorithm for each of the aerodynamic coefficients (lift, drag and moment). The artificial neural networks were integrated with a gradient-based optimizer. Using independent numerical simulations and experimental data for this high-lift configuration, it was shown that this design process successfully optimized flap deflection, gap, overlap, and angle of attack to maximize lift. Once the neural nets were trained and integrated with the optimizer, minimal additional computer resources were required to perform optimization runs with different initial conditions and parameters. Applying the neural networks within the high-lift rigging optimization process reduced the amount of computational time and resources by 44% compared with traditional gradient-based optimization procedures for multiple optimization runs.

Greenman, Roxana M.↗
NASA NTRS1998

High-Lift Optimization Design Using Neural Networks on a Multi-Element Airfoil

The high-lift performance of a multi-element airfoil was optimized by using neural-net predictions that were trained using a computational data set. The numerical data was generated using a two-dimensional, incompressible, Navier-Stokes algorithm with the Spalart-Allmaras turbulence model. Because it is difficult to predict maximum lift for high-lift systems, an empirically-based maximum lift criteria was used in this study to determine both the maximum lift and the angle at which it occurs. Multiple input, single output networks were trained using the NASA Ames variation of the Levenberg-Marquardt algorithm for each of the aerodynamic coefficients (lift, drag, and moment). The artificial neural networks were integrated with a gradient-based optimizer. Using independent numerical simulations and experimental data for this high-lift configuration, it was shown that this design process successfully optimized flap deflection, gap, overlap, and angle of attack to maximize lift. Once the neural networks were trained and integrated with the optimizer, minimal additional computer resources were required to perform optimization runs with different initial conditions and parameters. Applying the neural networks within the high-lift rigging optimization process reduced the amount of computational time and resources by 83% compared with traditional gradient-based optimization procedures for multiple optimization runs.

Greenman, Roxana M.↗
NASA NTRS2001

Cryogenic Treatment of Al-Li Alloys for Improved Weldability, Repairability, and Reduction of Residual Stresses

Service performance has shown that cryogenic treatment of some metals provides improved strength, fatigue life, and wear resistance to the processed material. Effects such as these were initially discovered by NASA engineers while evaluating spacecraft that had returned from the cold vacuum of space. Factors such as high cost, poor repairability, and poor machinability are currently prohibitive for wide range use of some aerospace aluminum alloys. Application of a cryogenic treatment process to these alloys is expected provide improvements in weldability and weld properties coupled with a reduction in repairs resulting in a significant reduction in the cost to manufacture and life cycle cost of aerospace hardware. The primary purpose of this effort was to evaluate the effects of deep cryogenic treatment of some aluminum alloy plate products, welds, and weld repairs, and optimize a process for the treatment of these materials. The optimized process is being evaluated for improvements in properties of plate and welds, improvements in weldability and repairability of treated materials, and as an alternative technique for the reduction of residual stresses in repaired welds. This paper will present the results of testing and evaluation conducted in this effort. These results will include assessments of changes in strength, toughness, stress corrosion susceptability, weldability, repairability, and reduction in residual stresses of repaired welds.

Malone, Tina W.↗
NASA NTRS1993

Optimizing the fine lock performance of the Hubble Space Telescope fine guidance sensors

This paper summarizes the on-orbit performance to date of the three Hubble Space Telescope Fine Guidance Sensors (FGS's) in Fine Lock mode, with respect to acquisition success rate, ability to maintain lock, and star brightness range. The process of optimizing Fine Lock performance, including the reasoning underlying the adjustment of uplink parameters, and the effects of optimization are described. The Fine Lock optimization process has combined theoretical and experimental approaches. Computer models of the FGS have improved understanding of the effects of uplink parameters and fine error averaging on the ability of the FGS to acquire stars and maintain lock. Empirical data have determined the variation of the interferometric error characteristics (so-called 's-curves') between FGS's and over each FGS field of view, identified binary stars, and quantified the systematic error in Coarse Track (the mode preceding Fine Lock). On the basis of these empirical data, the values of the uplink parameters can be selected more precisely. Since launch, optimization efforts have improved FGS Fine Lock performance, particularly acquisition, which now enjoys a nearly 100 percent success rate. More recent work has been directed towards improving FGS tolerance of two conditions that exceed its original design requirements. First, large amplitude spacecraft jitter is induced by solar panel vibrations following day/night transitions. This jitter is generally much greater than the FGS's were designed to track, and while the tracking ability of the FGS's has been shown to exceed design requirements, losses of Fine Lock after day/night transitions are frequent. Computer simulations have demonstrated a potential improvement in Fine Lock tracking of vehicle jitter near terminator crossings. Second, telescope spherical aberration degrades the interferometric error signal in Fine Lock, but use of the FGS two-thirds aperture stop restores the transfer function with a corresponding loss of throughput. This loss requires the minimum brightness of acquired stars to be about one magnitude brighter than originally planned.

Eaton, David J.↗