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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 415 records · Page 23

Optimal design of compact spur gear reductions

The optimal design of compact spur gear reductions includes the selection of bearing and shaft proportions in addition to gear mesh parameters. Designs for single mesh spur gear reductions are based on optimization of system life, system volume, and system weight including gears, support shafts, and the four bearings. The overall optimization allows component properties to interact, yielding the best composite design. A modified feasible directions search algorithm directs the optimization through a continuous design space. Interpolated polynomials expand the discrete bearing properties and proportions into continuous variables for optimization. After finding the continuous optimum, the designer can analyze near optimal designs for comparison and selection. Design examples show the influence of the bearings on the optimal configurations.

Savage, M.↗

Geometric Model for a Parametric Study of the Blended-Wing-Body Airplane

A parametric model is presented for the blended-wing-body airplane, one concept being proposed for the next generation of large subsonic transports. The model is defined in terms of a small set of parameters which facilitates analysis and optimization during the conceptual design process. The model is generated from a preliminary CAD geometry. From this geometry, airfoil cross sections are cut at selected locations and fitted with analytic curves. The airfoils are then used as boundaries for surfaces defined as the solution of partial differential equations. Both the airfoil curves and the surfaces are generated with free parameters selected to give a good representation of the original geometry. The original surface is compared with the parametric model, and solutions of the Euler equations for compressible flow are computed for both geometries. The parametric model is a good approximation of the CAD model and the computed solutions are qualitatively similar. An optimal NURBS approximation is constructed and can be used by a CAD model for further refinement or modification of the original geometry.

Mastin, C. Wayne↗

Amplitude- and frequency-dependent activation of layer II/III neurons by intracortical microstimulation

Intracortical microstimulation (ICMS) has been used for the development of brain machine interfaces. However, further understanding about the spatiotemporal responses of neurons to different electrical stimulation parameters is necessary to inform the design of optimal therapies. In this study, we employed in vivo electrophysiological recording, two-photon calcium imaging, and electric field simulation to evaluate the acute effect of ICMS on layer II/III neurons. Our results show that stimulation frequency non-linearly modulates neuronal responses, whereas the magnitude of responses is linearly correlated to the electric field strength and stimulation amplitude before reaching a steady state. Temporal dynamics of neurons’ responses depends more on stimulation frequency and their distance to the stimulation electrode. In addition, amplitude-dependent post-stimulation suppression was observed within ~500 μm of the stimulation electrode, as evidenced by both calcium imaging and local field potentials. These findings provide insights for selecting stimulation parameters to achieve desirable spatiotemporal specificity of ICMS.

59 BASIC BIOLOGICAL SCIENCES↗

Optimization Approach for Wind Tunnel Fan Blade Strain Gage Correlation with Test Fixture Unknowns

NASA has a significant maintenance challenge with the aging wind tunnel infrastructure across the Agency. Some wind tunnel fan blades, such as those in the National Transonic Facility at NASA Langley Research Center, have been in use for far longer than their planned 10-year lifetime. No detailed analytical models of the fan blades from their initial fabrication were created. To support the fabrication of either new, nominally identical fan blades or newly designed fan blades, accurate analytical models of the existing fan blades are necessary to demonstrate an understanding of the capabilities of the existing fan blades. Additionally, the existing documentation of the testing of the existing fan blades has gaps. In this report, a process for improving test-analysis correlation for these wind tunnel fan blades is discussed. This process involved a detailed study of unknown parameters in test fixture parameters from the old and incomplete test documentation. To improve correlation, these unknown parameters were used as design variables in an optimization study to minimize the error between test data and computed structural responses. Legacy strain gage data from tests conducted in 1981 were compared with results from a finite element model created in 2019. The use of test data from 1981 was necessary because none of the existing fan blades could be spared for use in destructive structural testing. While this process was demonstrated for wind tunnel fan blades, this process could be utilized for evaluating unknowns in test fixtures for other structural test configurations.

wind tunnel↗

Development and optimization of a nonlinear multiparameter model for the human operator

A systematic method is proposed for the development, optimization, and comparison of controller-models for the human operator. This is suitable for any designed model, even multiparameter systems. A random search technique is chosen for the parameter optimization. As valuation criteria for the quality of the model development the criterion function - the comparison between the input and output functions of the human operator and those of the model - and the most important characteristic values and functions of the statistical signal theory are used. A nonlinear multiparameter model for the human operator is being designed which considers the complex input information rate per time in a single display. The nonlinear features of the model are effected by a modified threshold element and a decision algorithm. Different display-configurations as well as various transfer functions of the controlled element are explained by different optimized parameter-combinations.

Johannsen, G.↗

A Design Framework for Thick and Thin Tow-Steered Composites Using Mechanics of Structure Genome

The design of tow-steered composites is one of the most popular and promising topics under the class of variable stiffness structures. In this work, the authors propose a new design framework and tool for the optimization of tow-steered composites. Mechanics of structure genome (MSG) provides accurate computation of plate/shell section properties including thick and highly curved structures. The computed section properties can be directly used in commercial computer-aided engineering tools. Tow-steered composites are modeled through a design framework wherein tow paths are parameterized in a general way and projected onto a finite element mesh, and MSG calculates the local shell/plate properties. The result is a complete workflow from design parameter input to structural performance evaluation. An open-source optimization software package is used to enable constrained optimization of structural stiffness for the broad tow-steered composite design space. Numerical examples are provided to demonstrate the capabilities of this tool and the promise and potential of tow-steered designs that optimize structural performance while satisfying manufacturing constraints.

Su Tian↗

A Design Framework for Thick and Thin Tow-Steered Composites Using Mechanics of Structure Genome

The design of tow-steered composites is one of the most popular and promising topics under the class of variable stiffness structures. In this work, the authors propose a new design framework and tool for the optimization of tow-steered composites. Mechanics of structure genome (MSG) provides accurate computation of plate/shell section properties including thick and highly curved structures. The computed section properties can be directly used in commercial computer-aided engineering tools. Tow-steered composites are modeled through a design framework wherein tow paths are parameterized in a general way and projected onto a finite element mesh, and MSG calculates the local shell/plate properties. The result is a complete workflow from design parameter input to structural performance evaluation. An open-source optimization software package is used to enable constrained optimization of structural stiffness for the broad tow-steered composite design space. Numerical examples are provided to demonstrate the capabilities of this tool and the promise and potential of tow-steered designs that optimize structural performance while satisfying manufacturing constraints.

Su Tian↗

Application of an equation‐oriented framework to formulate and estimate parameters of chemical looping reaction models

Abstract Accurate, predictive reaction models are critical for the design and optimization of chemical looping combustion (CLC) reactors. The formulation and estimation of kinetic parameters for these reaction models using a first‐principles equation‐oriented (EO) approach is particularly beneficial as large amounts of experimental data spanning process‐relevant conditions can be used to estimate parameters in a computationally tractable way. This work demonstrates the application of a novel EO framework to develop reduction reaction kinetic models of an iron‐based CLC oxygen carrier (OC). An optimization problem is formulated to estimate kinetic parameters that provide the best fit to the experimental data. The model predicts the state of the OC with mean square error values of 2.5%–4.4% across the full range of validation data, including multiple reduction cycles.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Bayesian experimental design and parameter estimation for ultrafast spin dynamics

Abstract Advanced experimental measurements are crucial for driving theoretical developments and unveiling novel phenomena in condensed matter and materials physics, which often suffer from the scarcity of large-scale facility resources, such as x-ray or neutron scattering centers. To address these limitations, we introduce a methodology that leverages the Bayesian optimal experimental design paradigm to efficiently uncover key quantum spin fluctuation parameters from x-ray photon fluctuation spectroscopy (XPFS) data. Our method is compatible with existing theoretical simulation pipelines and can also be used in combination with fast machine learning surrogate models in the event that real-time simulations are unfeasible. Our numerical benchmarks demonstrate the superior performance in predicting model parameters and in delivering more informative measurements within limited experimental time. Our method can be adapted to many different types of experiments beyond XPFS and spin fluctuation studies, facilitating more efficient data collection and accelerating scientific discoveries.

97 MATHEMATICS AND COMPUTING↗

An analytical sensitivity method for use in integrated aeroservoelastic aircraft design

Interdisciplinary analysis capabilities have been developed for aeroservoelastic aircraft and large flexible spacecraft, but the requisite integrated design methods are only beginning to be developed. One integrated design method which has received attention is based on hierarchal problem decompositions, optimization, and design sensitivity analyses. This paper highlights a design sensitivity analysis method for Linear Quadratic Gaussian (LQG) optimal control laws, enabling the use of LQG techniques in the hierarchal design methodology. The LQG sensitivity analysis method calculates the change in the optimal control law and resulting controlled system responses due to changes in fixed design integration parameters using analytical sensitivity equations. Numerical results of a LQG design sensitivity analysis for a realistic aeroservoelastic aircraft example are presented. In this example, the sensitivity of the optimal control law and aircraft response for various parameters such as wing bending natural frequency is determined. The sensitivity results computed from the analytical expressions are used to estimate changes in response resulting from changes in the parameters. Comparisons of the estimates with exact calculated responses show they are reasonably accurate for + or - 15 percent changes in the parameters. Evaluation of the analytical expressions is computationally faster than equivalent finite difference calculations.

Gilbert, Michael G.↗

An analytical sensitivity method for use in integrated aeroservoelastic aircraft design

Interdisciplinary analysis capabilities have been developed for aeroservoelastic aircraft and large flexible spacecraft, but the requisite integrated design methods are only beginning to be developed. One integrated design method which has received attention is based on hierarchal problem decompositions, optimization, and design sensitivity analyses. This paper highlights a design sensitivity analysis method for Linear Quadratic Gaussian (LQG) optimal control laws, enabling the use of LQG techniques in the hierarchal design methodology. The LQG sensitivity analysis method calculates the change in the optimal control law and resulting controlled system responses due to changes in fixed design integration parameters using analytical sensitivity equations. Numerical results of an LQG design sensitivity analysis for a realistic aeroservoelastic aircraft example are presented. In this example, the sensitivity of the optimal control law and aircraft response for various parameters such as wing bending natural frequency is determined. The sensitivity results computed from the analytical expressions are used to estimate changes in response resulting from changes in the parameters. Comparisons of the estimates with exact calculated responses show they are reasonably accurate for + or - 15 percent changes in the parameters. Evaluation of the analytical expressions is computationally faster than equivalent finite difference calculations.

Gilbert, Michael G.↗

Effects of pillar design on the thermal performance of vacuum-insulated glazing

Vacuum-insulated glazing (VIG) with a low-emittance coating has a great market potential as an effective transparent insulator. The thermal insulating performance of VIG is determined by its design, including material selection and configuration of different components. Thermal conductance of the vacuum gap as a transport bottleneck is one of the primary factors controlling the thermal transport across VIG. In particular, because support pillars provide the main thermal transport channels across the vacuum gap, increasing the pillar thermal resistance is a key strategy for creating effective thermal insulation while maintaining the vacuum space. Here, the effects of various pillar design parameters, such as thermal conductivity, geometry, and arrangement, on the VIG thermal performance were comprehensively investigated via the finite element method. In addition, analytical models for thermal transport were examined and thermal conductance across the VIG unit was experimentally measured for validation. The pillar design parameters, especially the height, shape, spacing, and arrangement of the pillars, showed significant effects on the thermal performance of VIG. This research also shows that the smaller contact area for horizontal pillars can effectively decrease the heat loss by more than 30%. Because current VIG analytical equations of thermal performance are only applicable to cylindrical pillars, an analytical equation that can better describe the thermal performance of rectangular parallelepiped pillars is presented, along with a discussion about the mechanism of thermal transfer for different pillar shapes. Thermo-mechanical analyses based on 3D FEM simulations can provide valuable insights into the effect of various design parameters on the overall performance the VIG, allowing for the development of an optimal VIG design.

36 MATERIALS SCIENCE↗

Melt Pool and Heat Treatment Optimization for the Fabrication of High-Strength and High-Toughness Additively Manufactured 4340 Steel

Additively manufactured (AM) components offer superior design flexibility compared to their conventionally manufactured counterparts, and optimizing processing parameters is key to achieving high-quality depositions with desirable and predictable mechanical properties. This study was focused on 4340 steel fabricated using laser powder bed fusion (LPBF), and 42 laser power and scan speed combinations have been systematically investigated to determine an optimized melt pool geometry that would ensure fully-dense parts. The AM material was compared with a wrought 4340 equivalent and studied in two customized heat treated conditions, optimized for strength and toughness, respectively. The microstructures of the as-fabricated and heat treated AM and wrought materials were characterized to assess differences introduced by the layer-by-layer fabrication process and subsequent heat treatment. Tensile properties of both materials were also evaluated and demonstrate that the AM materials offer equal or superior properties compared to the wrought equivalents. Differences in fracture surface morphologies indicate the distinct failure mechanisms associated with the materials’ characteristic microstructures, and the role of inclusions in the failures was studied to elucidate these differences. Complementary to the experimental investigations, the dataset was leveraged to make recommendations for future design of experiments to optimize AM build parameters in other material systems. A statistical Monte Carlo analysis was used to predict the interpolation error produced using reduced datasets and to enable informed processing parameters selection. These findings are discussed to make recommendations for the use of AM materials for high-integrity structural applications.

36 MATERIALS SCIENCE↗

Design of Multi-Parameter Steerable Functions Using Cascade Basis Reduction

A new cascade basis reduction method of computing the optimal least-squares set of basis functions steering a given function is presented. The method combines the Lie group-theoretic and the singular value decomposition approaches in such a way that their respective strengths complement each other. Since the Lie group-theoretic approach is used, the set of basis and steering functions computed can be expressed analytically. Because the singular value decomposition method is used, this set of basis and steering functions is optimal in the least-squares sense. Furthermore, the computational complexity in designing basis functions for transformation groups with large numbers of parameters is significantly reduced. The efficiency of the cascade basis reduction method is demonstrated by designing a set of basis functions that steers a Gabor function under the four-parameter linear transformation group.

Teo, P.↗

Structural modelling and control design under incomplete parameter information: The maximum-entropy approach

A stochastic structural control model is described. In contrast to the customary deterministic model, the stochastic minimum data/maximum entropy model directly incorporates the least possible a priori parameter information. The approach is to adopt this model as the basic design model, thus incorporating the effects of parameter uncertainty at a fundamental level, and design mean-square optimal controls (that is, choose the control law to minimize the average of a quadratic performance index over the parameter ensemble).

Hyland, D. C.↗

Floating Wind Turbine Control Optimization

We present a framework for optimizing the control parameters of floating offshore wind turbines (FOWTs). The framework combines aeroelastic simulations with a systems engineering model and control software. In an example of the optimization framework, we minimize tower damage equivalent loading with generator speed constraints. We also study the effect of thrust-limiting control and quantify the trade off between fatigue loading and energy capture using a set of optimal controller designs. Finally, we optimize the controller of four different FOWT models and compare their dynamic responses. Additional details and other use cases for the framework are presented, which can optimize different control problems and evaluate FOWT designs.

controls↗