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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 307 records · Page 17
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Fully self-consistent finite-temperature $GW$ in Gaussian Bloch orbitals for solids

In this work, we present algorithmic and implementation details for the fully self-consistent finite-temperature $GW$ method in Gaussian Bloch orbitals for solids. Our implementation is based on the finite-temperature Green's function formalism in which all equations are solved on the imaginary axis, without resorting to analytical continuation during the self-consistency. No quasiparticle approximation is employed and all matrix elements of the self-energy are explicitly evaluated. The method is tested by evaluating the band gaps of selected semiconductors and insulators. We show agreement with other, differently formulated, finite-temperature sc ⁢$GW$ implementations when finite-size corrections and basis-set errors are taken into account. By migrating computationally intensive calculations to graphics processing units, we obtain scalable results on large supercomputers with nearly optimal performance. Our work demonstrates the applicability of Gaussian orbital based sc⁢ $GW$ for ab initio correlated material simulations and provides a sound starting point for embedding methods built on top of $GW$.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2022

A simplified, efficient approach to hybrid wind and solar plant site optimization

Abstract. Wind plant layout optimization is a difficult, complex problem with a large number of variables and many local minima. Layout optimization only becomes more difficult with the addition of solar generation. In this paper, we propose a parameterized approach to wind and solar hybrid power plant layout optimization that greatly reduces problem dimensionality while guaranteeing that the generated layouts have a desirable regular structure. Thus far, hybrid power plant optimization research has focused on system sizing. We go beyond sizing and present a practical approach to optimizing the physical layout of a wind–solar hybrid power plant. We argue that the evolution strategy class of derivative-free optimization methods is well-suited to the parameterized hybrid layout problem, and we demonstrate how hard layout constraints (e.g., placement restrictions) can be transformed into soft constraints that are amenable to optimization using evolution strategies. Next, we present experimental results on four test sites, demonstrating the viability, reliability, and effectiveness of the parameterized evolution strategy approach for generating optimized hybrid plant layouts. Completing the tool kit for parameterized layout generation, we include a brief tutorial describing how the parameterized evolutionary approach can be inspected, understood, and debugged when applied to hybrid plant layouts.

14 SOLAR ENERGY↗
NASA NTRS1994

A structural design decomposition method utilizing substructuring

A new method of design decomposition for structural analysis and optimization is described. For this method, the structure is divided into substructures where each substructure has its structural response described by a structural-response subproblem, and its structural sizing determined from a structural-sizing subproblem. The structural responses of substructures that have rigid body modes when separated from the remainder of the structure are further decomposed into displacements that have no rigid body components, and a set of rigid body modes. The structural-response subproblems are linked together through forces determined within a structural-sizing coordination subproblem which also determines the magnitude of any rigid body displacements. Structural-sizing subproblems having constraints local to the substructures are linked together through penalty terms that are determined by a structural-sizing coordination subproblem. All the substructure structural-response subproblems are totally decoupled from each other, as are all the substructure structural-sizing subproblems, thus there is significant potential for use of parallel solution methods for these subproblems.

Scotti, Stephen J.↗
NASA NTRS1994

Aligning parallel arrays to reduce communication

Axis and stride alignment is an important optimization in compiling data-parallel programs for distributed-memory machines. We previously developed an optimal algorithm for aligning array expressions. Here, we examine alignment for more general program graphs. We show that optimal alignment is NP-complete in this setting, so we study heuristic methods. This paper makes two contributions. First, we show how local graph transformations can reduce the size of the problem significantly without changing the best solution. This allows more complex and effective heuristics to be used. Second, we give a heuristic that can explore the space of possible solutions in a number of ways. We show that some of these strategies can give better solutions than a simple greedy approach proposed earlier. Our algorithms have been implemented; we present experimental results showing their effect on the performance of some example programs running on the CM-5.

Sheffler, Thomas J.↗
NASA NTRS2014

Micro-Spec: an Integrated, Direct-Detection Spectrometer for Far-Infrared and Submillimeter Astronomy

The far-infrared and submillimeter portions of the electromagnetic spectrum provide a unique view of the astrophysical processes present in the early universe. Our ability to fully explore this rich spectral region has been limited, however, by the size and cost of the cryogenic spectrometers required to carry out such measurements. Micro-Spec (u-Spec) is a high-sensitivity, direct-detection spectrometer concept working in the 450-1000 micromillimeter wavelength range which will enable a wide range of flight missions that would otherwise be challenging due to the large size of current instruments with the required spectral resolution and sensitivity. The spectrometer design utilizes two internal antenna arrays, one for transmitting and one for receiving, superconducting microstrip transmission lines for power division and phase delay, and an array of microwave kinetic inductance detectors (MKIDs) to achieve these goals. The instrument will be integrated on a approximately 10 square cm silicon chip and can therefore become an important capability under the low background conditions accessible via space and high-altitude borne platforms. In this paper, an optical design methodology for Micro-Spec is presented, with particular attention given to its twodimensional diffractive region, where the light of different wavelengths is focused on the different detectors. The method is based on the maximization of the instrument resolving power and minimization of the RMS phase error on the instrument focal plane. This two-step optimization can generate geometrical configurations given specific requirements on spectrometer size, operating spectral range and performance. A point design with resolving power of 257, an RMS phase error less than 0.1 radians and four stigmatic points was developed for initial demonstration and will be the basis of future instruments with resolving power up to about 1200.

microwave kinetic inductance detectors (MKIDs)↗
NASA NTRS2001

Accuracy Assessment of Response Surface Approximations for Supersonic Turbine Design

There is a growing trend to employ CFD tools to supply the necessary information for design optimization of fluid dynamics components/systems. Such results are prone to uncertainties due to reasons including discretization. errors, incomplete convergence of computational procedures, and errors associated with physical models such as turbulence closures. Based on this type of information, gradient-based optimization algorithms often suffer from the noisy calculations, which can seriously compromise the outcome. Similar problems arise from the experimental measurements. Global optimization techniques, such as those based on the response surface (RS) concept are becoming popular in part because they can overcome some of these barriers. However, there are also fundamental issues related to such global optimization technique such as RS. For example, in high dimensional design spaces, typically only a small number of function evaluations are available due to computational and experimental costs. On the other hand, complex features of the design variables do not allow one to model the global characteristics of the design space with simple quadratic polynomials. Consequently a main challenge is to reduce the size of the region where we fit the RS, or make it more accurate in the regions where the optimum is likely to reside. Response Surface techniques using either polynomials or and Neural Network (NN) methods offer designers alternatives to conduct design optimization. The RS technique employs statistical and numerical techniques to establish the relationship between design variables and objective/constraint functions, typically using polynomials. In this study, we aim at addressing issues related to the following questions: (1) How to identify outliers associated with a given RS representation and improve the RS model via appropriate treatments? (2) How to focus on selected design data so that RS can give better performance in regions critical to design optimization? (3) How to combine NN and polynomial techniques for improving the accuracy of the RS model?

Papila, Nilay↗
NASA NTRS2014

Micro-spec: an Integrated Direct-detection Spectrometer for Far-infrared Space Telescopes

The far-infrared and submillimeter portions of the electromagnetic spectrum provide a unique view of the astrophysical processes present in the early universe. Our ability to fully explore this rich spectral region has been limited, however, by the size and cost of the cryogenic spectrometers required to carry out such measurements.Micro-Spec (μ-Spec) is a high-sensitivity, direct-detection spectrometer concept working in the 450-1000 (micrometers) wavelength range which will enable a wide range of flight missions that would otherwise be challenging due tothe large size of current instruments with the required spectral resolution and sensitivity. The spectrometer design utilizes two internal antenna arrays, one for transmitting and one for receiving, superconducting microstrip transmission lines for power division and phase delay, and an array of microwave kinetic inductance detectors (MKIDs) to achieve these goals. The instrument will be integrated on a approximately 10 sq cm silicon chip and can therefore become an important capability under the low background conditions accessible via space and high-altitude borne platforms. In this paper, an optical design methodology for micro-Spec is presented, with particular attention given to its two-dimensional diffractive region, where the light of different wavelengths is focused on the different detectors. The method is based on the maximization of the instrument resolving power and minimization of the RMS phase error on the instrument focal plane. This two-step optimization can generate geometrical configurations given specific requirements on spectrometer size, operating spectral range and performance.Two point designs with resolving power of 260 and 520 and an RMS phase error less than approximately 0.004 radians were developed for initial demonstration and will be the basis of future instruments with resolving power up to about 1200.

Far-infrared↗
DOE OSTI2024

Data-driven projection pursuit adaptation of polynomial chaos expansions for dependent high-dimensional parameters

Uncertainty quantification (UQ) and inference involving a large number of parameters are valuable tools for problems associated with heterogeneous and non-stationary behaviors. The difficulty with these problems is exacerbated when these parameters are statistically dependent requiring statistical characterization over joint measures. Probabilistic modeling methodologies stand as effective tools in the realms of UQ and inference. Among these, polynomial chaos expansions (PCE), when adapted to low-dimensional quantities of interest (QoI), provide effective yet accurate approximations for these QoI in terms of an adapted orthogonal basis. These adaptation techniques have been cast as projection pursuits in Gaussian Hilbert space in what has been referred to as a projection pursuit adaptation (PPA) by Xiaoshu Zeng and Roger Ghanem (2023). The PPA method efficiently identifies an optimal low-dimensional space for representing the QoI and simultaneously evaluates an optimal PCE within that space. The quality of this approximation clearly depends on the size of the training dataset, which is typically a function of the adapted reduced dimension. Here, the complexity of the problem is thus mediated by the complexity of the low-dimensional quantity of interest and not the complexity of the high-dimensional parameter space.

Data-driven↗
DOE OSTI2022

Natural gas maximal load delivery for multi-contingency analysis

An increasing dependence on natural gas has amplified existing vulnerabilities to the power grid, including disruptions to gas transmission networks from natural and man-made disasters. To address the operational challenges arising from these disruptions, we, in this study, consider the problem of estimating the steady-state operating capacity of a damaged gas pipeline network while ensuring the maximal delivery of load. Specifically, we formulate the mixed-integer nonconvex maximal load delivery (MLD) problem, which proves difficult to solve on large-scale networks. To address this challenge, we present a relaxation of the MLD problem and use it to determine bounds on the transport capacity of a gas pipeline system. A rigorous computational evaluation over network models ranging in size from 11 to 4,197 junctions shows that the relaxation-based method is suitable for analyzing the impacts of multi-contingency network disruptions, often converging to the optimal solution of the relaxation in less than ten seconds.

03 NATURAL GAS↗
DOE OSTI2025

Machine learning for reparameterization of multi-scale closures

Scientific machine learning (ML) is becoming increasingly useful in learning closure models for multi-scale physics problems; however, many ML approaches require a vast array of training data and can struggle with generalization and interpretability. Here, rather than learning an entire closure operator, we adopt an existing reduced-dimension model of the microphysics and learn an optimal re-parameterization of the solver. We demonstrate two approaches for training the reduced dimension closure model (1) an a priori method that optimizes the closure parameterization and the neural network parameters separately and (2) an a posteriori method that simultaneously optimizes both. Using the simulation of biomass pyrolysis as a motivating example, we show that the a posteriori method achieves better target losses and is less dependent on training dataset size for generalizability. We then demonstrate the impact that implementing this reparameterization has at the macroscale, showing improved predictive performance with no modification to the underlying macroscale solvers.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
NASA NTRS1976

Study of flutter related computational procedures for minimum weight structural sizing of advanced aircraft

Results of a study of the development of flutter modules applicable to automated structural design of advanced aircraft configurations, such as a supersonic transport, are presented. Automated structural design is restricted to automated sizing of the elements of a given structural model. It includes a flutter optimization procedure; i.e., a procedure for arriving at a structure with minimum mass for satisfying flutter constraints. Methods of solving the flutter equation and computing the generalized aerodynamic force coefficients in the repetitive analysis environment of a flutter optimization procedure are studied, and recommended approaches are presented. Five approaches to flutter optimization are explained in detail and compared. An approach to flutter optimization incorporating some of the methods discussed is presented. Problems related to flutter optimization in a realistic design environment are discussed and an integrated approach to the entire flutter task is presented. Recommendations for further investigations are made. Results of numerical evaluations, applying the five methods of flutter optimization to the same design task, are presented.

Oconnell, R. F.↗
NASA NTRS1991

Robust decentralized control laws for the ACES structure

Control system design for the Active Control Technique Evaluation for Spacecraft (ACES) structure at NASA Marshall Space Flight Center is discussed. The primary objective of this experiment is to design controllers that provide substantial reduction of the line-of-sight pointing errors. Satisfaction of this objective requires the controllers to attenuate beam vibration significantly. The primary method chosen for control design is the optimal projection approach for uncertain systems (OPUS). The OPUS design process allows the simultaneous tradeoff of five fundamental issues in control design: actuator sizing, sensor accuracy, controller order, robustness, and system performance. A brief description of the basic ACES configuration is given. The development of the models used for control design and control design for eight system loops that were selected by analysis of test data collected from the structure are discussed. Experimental results showing that very significant performance improvement is achieved when all eight feedback loops are closed are presented.

Collins, Emmanuel G., Jr.↗
NASA NTRS1995

An efficiency study of the simultaneous analysis and design of structures

The efficiency of the Simultaneous Analysis and Design (SAND) approach in the minimum weight optimization of structural systems subject to strength and displacement constraints as well as size side constraints is investigated. SAND allows for an optimization to take place in one single operation as opposed to the more traditional and sequential Nested Analysis and Design (NAND) method, where analyses and optimizations alternate. Thus, SAND has the advantage that the stiffness matrix is never factored during the optimization retaining its original sparsity. One of SAND's disadvantages is the increase in the number of design variables and in the associated number of constraint gradient evaluations. If SAND is to be an acceptable player in the optimization field, it is essential to investigate the efficiency of the method and to present a possible cure for any inherent deficiencies.

Striz, Alfred G.↗
NASA NTRS1996

Constraints in Genetic Programming

Genetic programming refers to a class of genetic algorithms utilizing generic representation in the form of program trees. For a particular application, one needs to provide the set of functions, whose compositions determine the space of program structures being evolved, and the set of terminals, which determine the space of specific instances of those programs. The algorithm searches the space for the best program for a given problem, applying evolutionary mechanisms borrowed from nature. Genetic algorithms have shown great capabilities in approximately solving optimization problems which could not be approximated or solved with other methods. Genetic programming extends their capabilities to deal with a broader variety of problems. However, it also extends the size of the search space, which often becomes too large to be effectively searched even by evolutionary methods. Therefore, our objective is to utilize problem constraints, if such can be identified, to restrict this space. In this publication, we propose a generic constraint specification language, powerful enough for a broad class of problem constraints. This language has two elements -- one reduces only the number of program instances, the other reduces both the space of program structures as well as their instances. With this language, we define the minimal set of complete constraints, and a set of operators guaranteeing offspring validity from valid parents. We also show that these operators are not less efficient than the standard genetic programming operators if one preprocesses the constraints - the necessary mechanisms are identified.

Janikow, Cezary Z.↗
NASA NTRS1997

A Model-Based Approach for the Measurement of Eye Movements Using Image Processing

This paper describes a video eye-tracking algorithm which searches for the best fit of the pupil modeled as a circular disk. The algorithm is robust to common image artifacts such as the droopy eyelids and light reflections while maintaining the measurement resolution available by the centroid algorithm. The presented algorithm is used to derive the pupil size and center coordinates, and can be combined with iris-tracking techniques to measure ocular torsion. A comparison search method of pupil candidates using pixel coordinate reference lookup tables optimizes the processing requirements for a least square fit of the circular disk model. This paper includes quantitative analyses and simulation results for the resolution and the robustness of the algorithm. The algorithm presented in this paper provides a platform for a noninvasive, multidimensional eye measurement system which can be used for clinical and research applications requiring the precise recording of eye movements in three-dimensional space.

Sung, Kwangjae↗
NASA NTRS2003

Efficient, Multi-Scale Designs Take Flight

Engineers can solve aerospace design problems faster and more efficiently with a versatile software product that performs automated structural analysis and sizing optimization. Collier Research Corporation's HyperSizer Structural Sizing Software is a design, analysis, and documentation tool that increases productivity and standardization for a design team. Based on established aerospace structural methods for strength, stability, and stiffness, HyperSizer can be used all the way from the conceptual design to in service support. The software originated from NASA s efforts to automate its capability to perform aircraft strength analyses, structural sizing, and weight prediction and reduction. With a strategy to combine finite element analysis with an automated design procedure, NASA s Langley Research Center led the development of a software code known as ST-SIZE from 1988 to 1995. Collier Research employees were principal developers of the code along with Langley researchers. The code evolved into one that could analyze the strength and stability of stiffened panels constructed of any material, including light-weight, fiber-reinforced composites.

Source record↗
NASA NTRS2014

Supersonic Wing Optimization Using SpaRibs

This research investigates the advantages of using curvilinear spars and ribs, termed SpaRibs, to design a supersonic aircraft wing-box in comparison to the use of classic design concepts that employ straight spars and ribs. The objective is to achieve a more efficient load-bearing mechanism and to passively control the deformation of the structure under the flight loads. Moreover, the use of SpaRibs broadens the design space and allows for natural frequencies and natural mode shape tailoring. The SpaRibs concept is implemented in a new optimization MATLAB-based framework referred to as EBF3SSWingOpt. This optimization scheme performs both the sizing and the shaping of the internal structural elements, connecting the optimizer with the analysis software. The shape of the SpaRibs is parametrically defined using the so called Linked Shape method. Each set of SpaRibs is placed in a one by one square domain of the natural space. The set of curves is subsequently transformed in the physical space for creating the wing structure geometry layout. The shape of each curve of each set is unique; however, mathematical relations link the curvature in an effort to reduce the number of design variables. The internal structure of a High Speed Commercial Transport aircraft concept developed by Boeing is optimized subjected to stress, subsonic flutter and supersonic flutter constraints. The results show that the use of the SpaRibs allows for the reduction of the aircraft's primary structure weight without violating the constraints. A weight reduction of about 15 percent is observed.

Locatelli, David↗
NASA NTRS2019

How Certain Physical Considerations Impact Aerostructural Wing Optimization

Wing design optimization has been studied extensively and is of continued interest as optimization tools are developed and become more accessible. In each of these studies, certain assumptions and simplifications are made to make the design problem tractable. However, it is difficult to find systematic studies in which several considerations are added or removed one at a time to study how much impact they have. In this work, we examine how certain physical considerations (viscous drag, wave drag, thrust loads, and inertial relief from structural, fuel, and engine masses), impact the aerostructural optimization results for three distinct aircraft wings. The goal is to help develop a rough idea of how important these physical considerations are. We do this using gradient-based optimization and a multidisciplinary design optimization framework, OpenMDAO. We use the open-source tool OpenAeroStruct that couples a vortex lattice method to a finite element method. We establish a baseline aerostructural design optimization problem then perform a series of optimizations, each with one physical consideration removed from the baseline case. We find that depending on the size of the aircraft and flight conditions, the importance of some of these physical considerations varies considerably whereas the importance of others do not. Specifically, the optimal designs change radically without proper viscous and wave drag considerations and smaller aircraft with more distributed propulsion are more affected by the inclusion of engine loads.

Aeropropulsion↗