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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 1,729 records · Page 96

Carbon Nanotubes on Titanium Substrates for Stray Light Suppression

A method has been developed for growing carbon nanotubes on a titanium substrate, which makes the nano tubes ten times blacker than the current state-of-the-art paints in the visible to near infrared. This will allow for significant improvement of stray light performance in scientific instruments, or any other optical system. Because baffles, stops, and tubes used in scientific observations often undergo loads such as vibration, it is critical to develop this surface treatment on structural materials. This innovation optimizes the carbon nano - tube growth for titanium, which is a strong, lightweight structural material suitable for spaceflight use. The steps required to grow the nanotubes require the preparation of the surface by lapping, and the deposition of an iron catalyst over an alumina stiction layer by e-beam evaporation. In operation, the stray light controls are fabricated, and nanotubes (multi-walled 100 microns in length) are grown on the surface. They are then installed in the instruments or other optical devices.

Hagopian, John↗

NASTRAN buckling analysis of a thin walled cylinder

The computer run time required for a buckling analysis using NASTRAN is considerably greater than for a linear static analysis of the same structure. It is very important to obtain an optimal model size for the structure being analyzed, such that the model is neither so large as to increase running time unnecessarily, nor so small as to hinder accuracy. The problem of critical load accuracy versus model complexity is considered for a thin walled cylinder, using both Level 12 and Level 15 NASTRAN releases.

Wight, R. B.↗

Developing Optimized Trajectories Derived from Mission and Thermo-Structural Constraints

In conjunction with NASA and the Department of Defense, the Johns Hopkins University Applied Physics Laboratory (JHU/APL) has been investigating analytical techniques to address many of the fundamental issues associated with solar exploration spacecraft and high-speed atmospheric vehicle systems. These issues include: thermo-structural response including the effects of thermal management via the use of surface optical properties for high-temperature composite structures; aerodynamics with the effects of non-equilibrium chemistry and gas radiation; and aero-thermodynamics with the effects of material ablation for a wide range of thermal protection system (TPS) materials. The need exists to integrate these discrete tools into a common framework that enables the investigation of interdisciplinary interactions (including analysis tool, applied load, and environment uncertainties) to provide high fidelity solutions. In addition to developing robust tools for the coupling of aerodynamically induced thermal and mechanical loads, JHU/APL has been studying the optimal design of high-speed vehicles as a function of their trajectory. Under traditional design methodology the optimization of system level mission parameters such as range and time of flight is performed independently of the optimization for thermal and mechanical constraints such as stress and temperature. A truly optimal trajectory should optimize over the entire range of mission and thermo-mechanical constraints. Under this research, a framework for the robust analysis of high-speed spacecraft and atmospheric vehicle systems has been developed. It has been built around a generic, loosely coupled framework such that a variety of readily available analysis tools can be used. The methodology immediately addresses many of the current analysis inadequacies and allows for future extension in order to handle more complex problems.

Lear, Matthew H.↗

Multidisciplinary design optimization using multiobjective formulation techniques

This report addresses the development of a multidisciplinary optimization procedure using an efficient semi-analytical sensitivity analysis technique and multilevel decomposition for the design of aerospace vehicles. A semi-analytical sensitivity analysis procedure is developed for calculating computational grid sensitivities and aerodynamic design sensitivities. Accuracy and efficiency of the sensitivity analysis procedure is established through comparison of the results with those obtained using a finite difference technique. The developed sensitivity analysis technique are then used within a multidisciplinary optimization procedure for designing aerospace vehicles. The optimization problem, with the integration of aerodynamics and structures, is decomposed into two levels. Optimization is performed for improved aerodynamic performance at the first level and improved structural performance at the second level. Aerodynamic analysis is performed by solving the three-dimensional parabolized Navier Stokes equations. A nonlinear programming technique and an approximate analysis procedure are used for optimization. The proceduredeveloped is applied to design the wing of a high speed aircraft. Results obtained show significant improvements in the aircraft aerodynamic and structural performance when compared to a reference or baseline configuration. The use of the semi-analytical sensitivity technique provides significant computational savings.

Chattopadhyay, Aditi↗

Experimental Validation of an Integrated Controls-Structures Design Methodology

The first experimental validation of an integrated controls-structures design methodology for a class of large order, flexible space structures is described. Integrated redesign of the controls-structures-interaction evolutionary model, a laboratory testbed at NASA Langley, was described earlier. The redesigned structure was fabricated, assembled in the laboratory, and experimentally tested against the original structure. Experimental results indicate that the structure redesigned using the integrated design methodology requires significantly less average control power than the nominal structure with control-optimized designs, while maintaining the required line-of-sight pointing performance. Thus, the superiority of the integrated design methodology over the conventional design approach is experimentally demonstrated. Furthermore, amenability of the integrated design structure to other control strategies is evaluated, both analytically and experimentally. Using Linear-Quadratic-Guassian optimal dissipative controllers, it is observed that the redesigned structure leads to significantly improved performance with alternate controllers as well.

Maghami, Peiman G.↗

Simultaneous analysis and design

Optimization techniques are increasingly being used for performing nonlinear structural analysis. The development of element by element (EBE) preconditioned conjugate gradient (CG) techniques is expected to extend this trend to linear analysis. Under these circumstances the structural design problem can be viewed as a nested optimization problem. There are computational benefits to treating this nested problem as a large single optimization problem. The response variables (such as displacements) and the structural parameters are all treated as design variables in a unified formulation which performs simultaneously the design and analysis. Two examples are used for demonstration. A seventy-two bar truss is optimized subject to linear stress constraints and a wing box structure is optimized subject to nonlinear collapse constraints. Both examples show substantial computational savings with the unified approach as compared to the traditional nested approach.

Haftka, R. T.↗

Simultaneous analysis and design

Optimization techniques are increasingly being used for performing nonlinear structural analysis. The development of element by element (EBE) preconditioned conjugate gradient (CG) techniques is expected to extend this trend to linear analysis. Under these circumstances the structural design problem can be viewed as a nested optimization problem. There are computational benefits to treating this nested problem as a large single optimization problem. The response variables (such as displacements) and the structural parameters are all treated as design variables in a unified formulation which performs simultaneously the design and analysis. Two examples are used for demonstration. A seventy-two bar truss is optimized subject to linear stress constraints and a wing box structure is optimized subject to nonlinear collapse constraints. Both examples show substantial computational savings with the unified approach as compared to the traditional nested approach.

Haftka, R. T.↗

Locating damaged members in a truss structure using modal test data - A demonstration experiment

An experiment is designed to demonstrate and verify the performance of the on-orbit assessment approach for large flexible space truss structures. The on-orbit assessment approach can be accomplished, in principle, with dynamic response information, structural identification methods, and model correlation techniques which produce an adjusted mathematical model. An optimal update of the structure model is formed using the response data, then examined to locate damaged members. The experiment uses a laboratory scale model truss structure which exhibits characteristics expected for large space truss structures. Vibration experiments are performed to generate response data for the damaged truss. The damage location approach is described, as well as analytical work performed in support of the vibration tests, the measured response of the test article, and some preliminary results.

Smith, Suzanne Weaver↗

Choosing Sensor Configuration for a Flexible Structure Using Full Control Synthesis

Optimal locations and types for feedback sensors which meet design constraints and control requirements are difficult to determine. This paper introduces an approach to choosing a sensor configuration based on Full Control synthesis. A globally optimal Full Control compensator is computed for each member of a set of sensor configurations which are feasible for the plant. The sensor configuration associated with the Full Control system achieving the best closed-loop performance is chosen for feedback measurements to an output feedback controller. A flexible structure is used as an example to demonstrate this procedure. Experimental results show sensor configurations chosen to optimize the Full Control performance are effective for output feedback controllers.

Lind, Rick↗

Advanced Modeling and Process-Materials Co-Optimization Strategies for Swing Adsorption Based Gas Separations

This project devised a computational framework for simultaneously co-optimizing pressure swing adsorption process designs along with the sorbent materials (specifically, metal-organic frameworks) to be employed in the associated packed bed columns. The materials optimization aspect involved search over a design space that can describe the material’s molecular structure, while the process optimization aspect considered various process degrees of freedom for steps arising in various cycle configurations. This framework was demonstrated on the separation of nitrogen and carbon dioxide, which arises ubiquitously in a multitude of post-combustion carbon capture and “blue” hydrogen production applications. Our results led to metal-organic framework molecular descriptor choices that are predicted to outperform standard structures used in practice, providing guidance for future metal-organic framework synthesis efforts.

20 FOSSIL-FUELED POWER PLANTS↗

Ultra‐Flexible Pixelated Perovskite Photodetectors Enabled by Honeycomb Polymer Grids for High‐Resolution Imaging

Abstract A nature‐inspired fabrication method based on a photolithography‐free flexible polymer grid is reported for high‐resolution pixelation of perovskite photodiode arrays with exceptional mechanical ductility and a morphology resembling that of natural compound eyes. The resulting pixelated perovskite photosensitive layer has a ≈1 µm pixel size with 2000 Pixels per inch (PPI) resolution when fully assembled as a photodetector array, delivering a detectivity of >10 13 Jones while providing cross‐talk free imaging. Using a polymer grid effectively releases stress on the perovskite platform, greatly increasing the mechanical agility of the otherwise brittle perovskite film. This novel fabrication methodology and device design offer new possibilities for applications in robotics, biomedical imaging, and virtual and augmented reality.

Zheng, Ding [Department of Chemistry and the Mater↗

Modeling Water Uptake and Pt Utilization in High Surface Area Carbon

Local transport losses limit high-current density performance of fuel-cells, especially at low Pt-loadings. Optimizing catalyst-layer structure and material properties to mitigate these losses is critical for wide-scale fuel-cell commercialization. Carbon supports form the primary porous structure of catalyst layers in which Pt particles are deposited and ionomer films are distributed. Unlike non-porous carbon supports, high surface area carbon support is unique in its relative humidity dependent Pt utilization and performance due to presence of Pt particles in the micropores interior of carbon particles. We model water uptake and Pt utilization in catalyst layers with high-surface-area carbon support. Interactions between functional groups on the carbon pore walls and water play a vital role in controlling water uptake from water vapor by catalyst layers. Ionomer is shown to influence proton access in micropores, even though it may not deposit into the micropores.

08 HYDROGEN↗

Design optimization studies using COSMIC NASTRAN

The purpose of this study is to create, test and document a procedure to integrate mathematical optimization algorithms with COSMIC NASTRAN. This procedure is very important to structural design engineers who wish to capitalize on optimization methods to ensure that their design is optimized for its intended application. The OPTNAST computer program was created to link NASTRAN and design optimization codes into one package. This implementation was tested using two truss structure models and optimizing their designs for minimum weight, subject to multiple loading conditions and displacement and stress constraints. However, the process is generalized so that an engineer could design other types of elements by adding to or modifying some parts of the code.

Pitrof, Stephen M.↗

Active learning of ternary alloy structures and energies

Abstract Machine learning models with uncertainty quantification have recently emerged as attractive tools to accelerate the navigation of catalyst design spaces in a data-efficient manner. Here, we combine active learning with a dropout graph convolutional network (dGCN) as a surrogate model to explore the complex materials space of high-entropy alloys (HEAs). We train the dGCN on the formation energies of disordered binary alloy structures in the Pd-Pt-Sn ternary alloy system and improve predictions on ternary structures by performing reduced optimization of the formation free energy, the target property that determines HEA stability, over ensembles of ternary structures constructed based on two coordinate systems: (a) a physics-informed ternary composition space, and (b) data-driven coordinates discovered by the Diffusion Maps manifold learning scheme. Both reduced optimization techniques improve predictions of the formation free energy in the ternary alloy space with a significantly reduced number of DFT calculations compared to a high-fidelity model. The physics-based scheme converges to the target property in a manner akin to a depth-first strategy, whereas the data-driven scheme appears more akin to a breadth-first approach. Both sampling schemes, coupled with our acquisition function, successfully exploit a database of DFT-calculated binary alloy structures and energies, augmented with a relatively small number of ternary alloy calculations, to identify stable ternary HEA compositions and structures. This generalized framework can be extended to incorporate more complex bulk and surface structural motifs, and the results demonstrate that significant dimensionality reduction is possible in thermodynamic sampling problems when suitable active learning schemes are employed.

Chemistry↗

Curing process and pore structure of metakaolin-based geopolymers: Liquid-state 1H NMR investigation

Geopolymers are emerging construction materials with lower carbon dioxide emissions compared to the conventional cementitious materials. The knowledge of the curing process and the related pore structures are important for optimizing the properties of these materials for different applications. The curing process and final pore structure are sensitive to the amount of used water, however the specifics are unclear. The curing process and pore structures of metakaolin-based geopolymers with a narrow water-to-solid (w/s) ratio (0.59–0.66) were monitored by nuclear magnetic resonance (NMR) relaxometry and cryoporometry. The 14-day curing process was investigated by monitoring the change of T{sub 2} and T{sub 1} relaxation times and water signal intensity. After the curing, the pore structures were characterized by 2D T{sub 1}-T{sub 2} correlation and T{sub 2}-T{sub 2} exchange measurements of absorbed water. The pore size distributions (PSDs) were measured with NMR cryoporometry and compared to nitrogen physisorption and mercury intrusion porosimetry (MIP) results. We found that the relaxation times decreased as the pore structure of the geopolymers matured during the curing while the dissolution and the condensation periods of the curing were distinguished by the changes in signal amplitude reflecting the proton density. After the curing, three distinct pore sizes and connectivity between pores were identified from T{sub 1}-T{sub 2} and T{sub 2}-T{sub 2} spectra. Their PSDs were measured, and they were found to correspond to two different pore sizes originating from the arrangement of clusters and defective pores. In the narrow w/s ratio (0.59–0.66), the curing times were the same for all samples when cured at 24 °C while the pore sizes were observed to increase as a function of the w/s ratio.

36 MATERIALS SCIENCE↗

Algorithms for structural natural-frequency design

The algorithms used in the Jet Propulsion Laboratory (JPL) Iterative Design of Antenna Structures (IDEAS) program are furnished. The algorithms are based upon the operational research method of optimality criteria and the structural analysis method of virtual work. Examples of the natural frequency constrained design of an antenna tripod structure are included.

Levy, R.↗

PDEMOD: Software for control/structures optimization

Because of the possibility of adverse interaction between the control system and the structural dynamics of large, flexible spacecraft, great care must be taken to ensure stability and system performance. Because of the high cost of insertion of mass into low earth orbit, it is prudent to optimize the roles of structure and control systems simultaneously. Because of the difficulty and the computational burden in modeling and analyzing the control structure system dynamics, the total problem is often split and treated iteratively. It would aid design if the control structure system dynamics could be represented in a single system of equations. With the use of the software PDEMOD (Partial Differential Equation Model), it is now possible to optimize structure and control systems simultaneously. The distributed parameter modeling approach enables embedding the control system dynamics into the same equations for the structural dynamics model. By doing this, the current difficulties involved in model order reduction are avoided. The NASA Mini-MAST truss is used an an example for studying integrated control structure design.

Taylor, Lawrence W., Jr.↗